Related papers: An Event-Driven Framework for Business Awareness M…
Imagine interconnected objects with embedded artificial intelligence (AI), empowered to sense the environment, see it, hear it, touch it, interact with it, and move. As future networks of intelligent objects come to life, tremendous new…
Management is a complex task in today's heterogeneous and large scale networks like Cloud, IoT, vehicular and MPLS networks. Likewise, researchers and developers envision the use of artificial intelligence techniques to create cognitive and…
A model is a simplified representation of portion of reality that hides a system s nonessential characteristics. It provides a means for reducing complexity as well as visualization and communication and a basis for building it. Most models…
In this work, we introduce the Time-Aware World Model (TAWM), a model-based approach that explicitly incorporates temporal dynamics. By conditioning on the time-step size, {\Delta}t, and training over a diverse range of {\Delta}t values --…
Event prediction is the ability of anticipating future events, i.e., future real-world occurrences, and aims to support the user in deciding on actions that change future events towards a desired state. An event prediction method learns the…
Due to the rapid growth of social media platforms, these tools have become essential for monitoring information during ongoing disaster events. However, extracting valuable insights requires real-time processing of vast amounts of data. A…
Coordinating robotic swarms in dynamic and communication-constrained environments remains a fundamental challenge for collective intelligence. This paper presents a novel framework for event-triggered organization, designed to achieve…
In corporations around the world, the topic of cybersecurity and information security is becoming increasingly important as the number of cyberattacks on themselves continues to grow. Nowadays, it is no longer just a matter of protecting…
Occlusion-aware prediction remains a critical challenge in autonomous driving due to the inherent uncertainty of unobserved regions. Existing approaches either overestimate risk based on reachable states or struggle to predict accurate…
To address the issues of high interruption time and measurement report overhead under user equipment (UE) mobility especially in high speed 5G use cases the use of AI/ML techniques (AI/ML beam management and mobility procedures) have been…
Beam management is a challenging task for millimeter wave (mmWave) and sub-terahertz communication systems, especially in scenarios with highly-mobile users. Leveraging external sensing modalities such as vision, LiDAR, radar, position, or…
The need for improved network situational awareness has been highlighted by the growing complexity and severity of cyber-attacks. Mobile phones pose a significant risk to network situational awareness due to their dynamic behaviour and lack…
Quantifying emergence and modeling emergent dynamics in a data-driven manner for complex dynamical systems is challenging due to the lack of direct observations at the micro-level. Thus, it's crucial to develop a framework to identify…
We propose a computational model to estimate a person's attended awareness of their environment. We define attended awareness to be those parts of a potentially dynamic scene which a person has attended to in recent history and which they…
Nowadays, traffic management in urban areas is one of the major economic problems. In particular, when faced with emergency situations like firefighting, timely and efficient traffic dispatching is crucial. Intelligent coordination between…
The real-time data collection and automation capabilities offered by the Internet of Things (IoT) are revolutionizing and transforming Business Processes (BPs) into IoT-enhanced BPs, showing high potential for improving sustainability.…
In a dynamic heterogeneous environment, such as pervasive and ubiquitous computing, context-aware adaptation is a key concept to meet the varying requirements of different users. Connectivity is an important context source that can be…
The rapid development of cutting-edge technologies, the increasing volume of data and also the availability and processability of new types of data sources has led to a paradigm shift in data-based management and decision-making. Since…
Large language models (LLMs) are increasingly deployed as intelligent agents that reason, plan, and interact with their environments. To effectively scale to long-horizon scenarios, a key capability for such agents is a memory mechanism…
Context-Aware Emotion Recognition (CAER) is a crucial and challenging task that aims to perceive the emotional states of the target person with contextual information. Recent approaches invariably focus on designing sophisticated…