Recommender systems (RS) play an integral role in many online platforms. Exponential growth and potential commercial interests are raising significant concerns around privacy, security, fairness, and overall responsibility. The existing literature around responsible recommendation services is diverse and multi-disciplinary. Most literature reviews cover a specific aspect or a single technology for

The entire Image Signal Processor (ISP) of a camera relies on several processes to transform the data from the Color Filter Array (CFA) sensor, such as demosaicing, denoising, and enhancement. These processes can be executed either by some hardware or via software. In recent years, Deep Learning(DL) has emerged as one solution for some of them or even to replace the entire ISP using a single neural

Multi-Agent Reinforcement Learning (MARL) is susceptible to Adversarial Machine Learning (AML) attacks. Execution-time AML attacks against MARL are complex due to effects that propagate across time and between agents. To understand the interaction between AML and MARL, this survey covers attacks and defences for MARL, Multi-Agent Learning (MAL), and Deep Reinforcement Learning (DRL). This survey proposes

Procedural content generation (PCG) can be applied to a wide variety of tasks in games, from narratives, levels and sounds, to trees and weapons. A large amount of game content is comprised of graphical assets , such as clouds, buildings or vegetation, that do not require gameplay function considerations. There is also a breadth of literature examining the procedural generation of such elements for

Artificial intelligence (AI), and especially its sub-field of Machine Learning (ML), are impacting the daily lives of everyone with their ubiquitous applications. In recent years, AI researchers and practitioners have introduced principles and guidelines to build systems that make reliable and trustworthy decisions. From a practical perspective, conventional ML systems process historical data to extract

Purpose This study proposes and tests a model to analyse whether achievement, social and immersion motivational affordances embedded in gamified review platforms motivate consumers to altruistically create content in the post-consumption stage. Design/methodology/approach We used data from a sample of 343 reviewers and employed SmartPLS to test the research model. Findings Findings revealed that, while

Purpose The conventional notion that adopting Artificial Intelligence (AI) positively affects firm performance is often confronted with various examples of failures. In this context, large-scale empirical evidence of the economic performance implications of adopting AI is poor, especially in the context of Small and Medium Sized Enterprises (SMEs). Drawing upon the Resource-Based View and the Digital

Purpose With growing concerns about users’ well-being on social media, research stresses the importance of threat appraisals as a crucial first step in motivating self-protective actions. This study, in view of the prevalence of parasocial relationships between followers and social media influencers, aims to unravel the complex dynamics of followers’ threat perceptions within these relationships. Specifically

Purpose This study disentangles the impact of consumers’ adoption of mini-program channels on social media on their purchase behavior in e-marketplaces from a multichannel retailer’s perspective and examines the moderating roles of two types of brand messages (informational and transformational messages). Design/methodology/approach Based on 2,204 transaction records from a Chinese multichannel retailer

The open and broadcast nature of wireless mediums introduces significant security vulnerabilities, making authentication a critical concern in wireless networks. In recent years, Physical-Layer Authentication (PLA) techniques have garnered considerable research interest due to their advantages over Upper-Layer Authentication (ULA) methods, such as lower complexity, enhanced security, and greater compatibility

Vision is the most important sense for people, and it is also one of the main ways of cognition. As a result, people tend to utilize visual content to capture and share their life experiences, which greatly facilitates the transfer of information. Meanwhile, it also increases the risk of privacy violations, e.g., an image or video can reveal different kinds of privacy-sensitive information. Scholars

Purpose Advancements in augmented reality (AR) technology have increased the interest in improving brand equity by creating AR-enhanced branding experiences. However, despite the potential of AR branding, knowledge regarding the underlying mechanisms required for AR features to build brand equity remains limited. Thus, we considered embodied cognition theory to investigate how designing AR features

Distributed machine learning on edges is widely used in intelligent transportation, smart home, industrial manufacturing, and underground pipe network monitoring to achieve low latency and real time data processing and prediction. However, the presence of a large number of sensing and edge devices with limited computing, storage, and communication capabilities prevents the deployment of huge machine

Caching content at the edge network is a popular and effective technique widely deployed to alleviate the burden of network backhaul, shorten service delay and improve service quality. However, there has been some controversy over privacy violations in caching content at the edge network. On the one hand, the multi-access open edge network provides an ideal entrance or interface for external attackers

Process mining (PM) comprises a variety of methods for discovering information about processes from their execution logs. Some of them, such as trace clustering, trace classification, and anomalous trace detection require a preliminary preprocessing step in which the raw data is encoded into a numerical feature space. To this end, encoding techniques are used to generate vectorial representations of

Purpose The emergence of social media platforms has revolutionized how brands develop partnerships with social media influencers (SMIs). However, users are seeking more meaningful engagement with SMIs, and little is known about how brands can shift their focus from transient engagements to continued engagement that builds long-term brand–consumer relationships. Extant research has provided inconsistent

Recently, foundation language models (LMs) have marked significant achievements in the domains of natural language processing (NLP) and computer vision (CV). Unlike traditional neural network models, foundation LMs obtain a great ability for transfer learning by acquiring rich commonsense knowledge through pre-training on extensive unsupervised datasets with a vast number of parameters. Despite these

Recently, Artificial Intelligence Generated Content (AIGC) has gained significant attention from society, especially with the rise of Generative AI (GAI) techniques such as ChatGPT, GPT-4 [165], DALL-E-3 [184], and Sora [137]. AIGC involves using AI models to create digital content, such as images, music, and natural language, with the goal of making the content creation process more efficient and

The rapid development of deep learning has driven significant progress in image semantic segmentation—a fundamental task in computer vision. Semantic segmentation algorithms often depend on the availability of pixel-level labels (i.e., masks of objects), which are expensive, time-consuming, and labor-intensive. Weakly-supervised semantic segmentation (WSSS) is an effective solution to avoid such labeling

Adversarial binaries are executable files that have been altered without loss of function by an AI agent in order to deceive malware detection systems. Progress in this emergent vein of research has been constrained by the complex and rigid structure of executable files. Although prior work has demonstrated that these binaries deceive a variety of malware classification models which rely on disparate

LiDAR has gained popularity in autonomous driving due to advantages like long measurement distance, rich 3D information, and stability in harsh environments. Place Recognition (PR) enables vehicles to identify previously visited locations despite variations in appearance, weather, and viewpoints, even determining their global location within prior maps. This capability is crucial for accurate localization

The Internet of Bio-Nano Things (IoBNT) is collaborative cell biology and nanodevice technology interacting through Molecular Communication (MC). The IoBNT can be accomplished by using the Information and Communication Theory (ICT) study of biological networks. Various technologies such as the Internet of Nano Things (IoNT), the Internet of Bio-degradable Things (IoBDT) and the Internet of Ingestible

Purpose Benefiting from the development and innovation of artificial intelligence and affective computing technology, social chatbots that integrate cognitive analysis and affective social services have flooded into the consumer market. For cognition and emotion-oriented tasks, social chatbots do not always receive positive consumer responses. In addition, consumers have a contradictory attitude toward

Purpose In the past decade, the use of neurophysiological measures as a complementary source of information has contributed to our understanding of human–computer interaction. However, less attention has been given to their capability in providing measures with high temporal resolution. Two studies are designed to address the challenge of measuring users’ cognitive load in an online shopping environment

Purpose Short-form video advertisements have recently gained popularity and are widely used. However, creating attractive short video advertisements remains a challenge for sellers. Based on the visual-audio perspective and signaling theory, this study investigated the impacts of three visual features (number of shots, pixel-level image complexity and vertical versus horizontal formats) and two audio

The evolving landscape of educational technologies has ushered Virtual Reality (VR) in the forefront of higher education. As the COVID-19 pandemic propelled a rapid shift toward e-learning, the demand for high-quality distance education has surged, prompting an exploration of VR as a viable solution. While existing research indicates that VR supports student engagement and learning experiences compared

Engaging students in online discussion forums with social support holds significant potential for preventing and alleviating student burnout. However, the mechanisms by which different types of social support influence learning burnout remain poorly understood. Additionally, existing methods for detecting social support detection are limited in both practical application and theoretical advancement

Wireless Sensor Networks (WSNs) represent an innovative technology that integrates compact, energy-efficient sensors with wireless communication functionalities, facilitating instantaneous surveillance and data gathering from the surrounding environment. WSNs are utilized across diverse domains, such as environmental monitoring, industrial automation, healthcare, smart agriculture, home automation

Self-regulated learning has significant importance in blended learning, necessitating an exploration into the effects of metacognition on SRL. Furthermore, SRL exhibits interdependence, thus highlighting the urgent need for research that can capture the temporal processes of SRL in multi-task activities during blended learning. Over 18 weeks, 44 students participated in three SRL tasks designed for

Purpose This study aims to examine the cultural and economic circumstances that shape esports consumer agency through case studies of “experiential consumption” (Miles, 2021). Design/methodology/approach A multiple-case study approach (Stake, 2006) is deployed alongside participant observation and document analysis to identify three cases of experiential consumption in esports – an esports tournament

In the ever-evolving information technology landscape, the Internet of Things (IoT) is a groundbreaking concept that bridges the physical and digital worlds. It is the backbone of an increasingly sophisticated interactive environment, yet it is a subject of intricate security challenges spawned by its multifaceted manifestations. Central to securing IoT infrastructures is the crucial aspect of authentication

Low-rate threats are a class of attack vectors that are disruptive and stealthy, typically crafted for security vulnerabilities. They have been the significant concern for cyber security, impacting both conventional IP-based networks and emerging Software-Defined Networking (SDN). SDN is a revolutionary architecture that separates the control and data planes, offering advantages such as enhanced manageability

Enterprise Architecture (EA) is a systematic and holistic approach to designing and managing an organization's information systems components, aiding in optimizing resources, managing risk, and facilitating change. It weighs different architectural quality attributes against each other to achieve the most advantageous architecture. However, the evaluation of EA lacks a systematic approach. This study

Object selection and manipulation are the foundation of VR interactions. With the rapid development of VR technology and the field of virtual object selection and manipulation, the literature demands a structured understanding of the core research challenges and a critical reflection of the current practices. To provide such understanding and reflections, we systematically reviewed 106 papers. We identified

Scholars have recommended the application of an intelligent tutoring and instant feedback system (ITIFS) to enhance students' motor skills performance by automatically evaluating their learning performance and providing personalized guidance and feedback. However, solely providing personalized evaluation and feedback may not necessarily attract students' active and sustained engagement in practice

Purpose Online patient reviews are of considerable importance on online health platforms. However, there is limited understanding of how these reviews are generated and their impact on patients' choices of physicians. Therefore, this study aims to investigate the antecedents and consequences of online patient reviews on online health platforms. Design/methodology/approach This study introduced an online

Purpose Multiple crowdfunding platforms have been created over the last decade. Some have become extremely successful, but many others have failed. This study focuses on those strategic choices that founders of crowdfunding platforms need to make early on and which determine the basic characteristics of a platform. Specifically, it examines which combination(s) of these initial strategic choices shape(s)

Large foundation models, including large language models, vision transformers, diffusion, and LLM-based multimodal models, are revolutionizing the entire machine learning lifecycle, from training to deployment. However, the substantial advancements in versatility and performance these models offer come at a significant cost in terms of hardware resources. To support the growth of these large models

Administrator-centered access control failures can cause data breaches, putting organizations at risk of financial loss and reputation damage. Existing graphical policy configuration tools and automated policy generation frameworks attempt to help administrators configure and generate access control policies by avoiding such failures. However, graphical policy configuration tools are prone to human

This study conceptualizes e-Government maturity from the theoretical lens of strategic change. Drawing on a multiplicity of theories, it undertakes a fuzzy-set Qualitative Comparative Analysis of the drivers of e-Government maturity over the 2010–2020 decade. It bypasses partially conflicting findings about the contribution of human capital to high levels of e-Government maturity by showcasing instead

In recent years, machine learning (ML) has witnessed a paradigm shift in kernel function selection, which is pivotal in optimizing various ML models. Despite multiple studies about its significance, a comprehensive understanding of kernel function selection, particularly about model performance, still needs to be explored. Challenges remain in selecting and optimizing kernel functions to improve model

Digital games can help students learn how to cope with misinformation. However, misinformation games typically include multiple game mechanics, making it hard to identify which mechanics contribute to learning. Hence, the aim of this study was to clarify how misinformation games promote learning by examining the effects of two promising misinformation game mechanics– simulating evaluation strategies

Purpose The metaverse enables users to create their own avatars in a shared virtual space, giving rise to a new avatar personality that differs from their real-self personality. The aim of this research is to explore how users' real-self and avatar personalities may affect their behavioral engagement and satisfaction in the metaverse context. Design/methodology/approach This research applies self-discrepancy

Recent advancements in wireless communication technologies have made Wi-Fi signals indispensable in both personal and professional settings. The utilization of these signals for Human Activity Recognition (HAR) has emerged as a cutting-edge technology. By leveraging the fluctuations in Wi-Fi signals for HAR, this approach offers enhanced privacy compared to traditional visual surveillance methods.

Decentralized finance (DeFi) represents a novel financial system but faces significant fraud challenges, leading to substantial losses. Recent advancements in artificial intelligence (AI) show potential for complex fraud detection. Despite growing interest, a systematic review of these methods is lacking. This survey correlates fraud types with DeFi project stages, presenting a taxonomy based on the