Abstracts:Spatial audio has become a critical component of immersive computing, with growing use in virtual reality, gaming, telepresence, accessibility, and media. This article outlines the core technologies (binaural rendering, ambisonics, and object-based formats) and explains how human spatial perception informs system design. Key acoustic concepts, such as reverberation, timbre, and impulse response are discussed in relation to implementation. For IT professionals, spatial audio offers new opportunities to improve user experience but presents challenges in hardware, personalization, and integration. The article offers practical guidance on adopting spatial audio through format-agnostic pipelines, head-related transfer function tuning, perceptual rendering strategies, and inclusive design.

Abstracts:The widespread adoption of multi-cloud architectures has necessitated effective interoperability among diverse cloud services. The article delves into the methods, obstacles, and solutions associated with using various cloud environments. It represents the integration strategies adopted by contemporary organizations, the difficulties of ensuring consistent service delivery across multiple clouds, and the level of current implementation. This article pursues a detailed analysis of the present-day multi-cloud integration as well as a review of potential future research directions to increase its efficiency.

Abstracts:The rapid advancement of information technologies has accelerated the adoption of innovative solutions like serverless computing (SC). SC and artificial intelligence (AI) act as complementary technologies: SC offers scalable and cost-effective infrastructure for AI models, while AI enhances and automates serverless systems. This paper reviews how AI improves SC architectures and how SC supports AI deployment. The findings highlight mutual benefits in terms of efficiency, cost, and scalability.

Abstracts:This article presents a comprehensive coverage on Trojan classification and its detection techniques for CAD high-level synthesis (HLS) based intellectual property (IP) designs. The presented article highlights the state-of-the-art IP (hardware) Trojan types, their covert insertion sites in the design process, their payloads, as well as the detective countermeasure employed in the literature. The article also succinctly describes the threat model tackled in each HLS-IP Trojan detection technique along with its approach/functionality. The article finally provides a qualitative and quantitative analysis of each Trojan detection technique along with its comparison.

Abstracts:Data spaces have emerged as pivotal elements promoting data-driven applications and driving the growth of the data economy. Opposite to traditional data exchange, where trustworthiness relies on a central entity acting as a data transactions’ moderator, the decentralization introduced by data spaces overcomes the barriers for a worldwide market of data economy, ensuring the self-sovereignty for data owners. However, existing solutions for the deployment of data spaces jeopardize their adoption, isolating the data economy in different regions. This article delves into cross-data space interworking between International Data Spaces (IDS) and Connector Architecture for Decentralized Data Exchange (CADDE) architectures as they are the references, in Europe and Japan, respectively, for the creation of this kind of data sharing ecosystems. The article describes a CO2 footprint assessment case study—the first of its kind as far as we know—enabling cross-domain data exchange between different data spaces and discusses the pilot results.

Abstracts:This study explores the impact of large language models (LLMs) on emotion lexicon word vectorization on Turkish and English. Emotion analysis involves extracting affective information from various data sources, with text being a primary medium. While traditional vectorization methods lack semantic meaning, contextual vectors, such as bidirectional encoder representations from transformers (BERT), aim to capture the context of words, leading to improved performance in natural language processing tasks. We investigate the efficacy of context sentences from human-annotated datasets and sentences generated by Gemini-Pro LLM in creating word vectors. Additionally, we introduce a manually annotated Turkish emotion and sentiment lexicon (TES-Lex). Performance evaluation is conducted for both Turkish and English using BERT vectors with two approaches: cosine similarity and machine learning. Our findings indicate that LLM-generated context sentences significantly enhance the quality of word vectors, especially in Turkish, underscoring the potential of LLMs in augmenting emotion lexicon resources in low-resourced languages.

Abstracts:The Middle East and Africa (MEA) region presents a unique set of needs and opportunities for generative artificial intelligence (AI), driven by economic diversification, digital transformation, and social challenges. Key sectors such as health care, education, finance, and governance require AI-driven solutions tailored to linguistic, cultural, and infrastructural nuances. In the Middle East, AI is central to national visions like Saudi Arabia’s Vision 2030 and the United Arab Emirates’s (UAE’s) AI strategy, strengthening innovation in smart cities and cybersecurity. Africa, with its diverse economies and growing tech hubs, demands AI for localized content creation, agricultural optimization, and financial inclusion. Addressing data scarcity, ethical AI deployment, and skill development remains critical for Africa. A region-specific approach to generative AI can enhance economic growth, societal well-being, and sustainable development in MEA.

Abstracts:Although artificial intelligence (AI)-driven technologies offer opportunities to improve efficiency and streamline government services, skepticism and job displacement concerns remain prevalent among frontline workers. Drawing on a survey of 205 respondents in quarter four of 2024, this study examines the factors driving AI resistance, the role of policy interventions, and the strategies available to bridge the digital gap for inclusive AI adoption in government in Africa. The findings show that blue-collar government employees have moderate awareness of AI’s potential but strong resistance, driven by fears of redundancy, low AI literacy, and limited upskilling opportunities. Older workers appear more resistant, while younger employees seem more open to adoption. Although employees recognized AI’s ability to improve service delivery, they opposed automation of routine tasks and criticized theoretical, nonpractical training. The study recommends structured AI literacy and hands-on training programs, alongside a centralized governance framework to ensure ethical, context-sensitive adoption.