Related papers: From Sensing to Decision: A Generic Architecture f…
Deterministic databases enable scalable replicated systems by executing transactions in a predetermined order. However, existing designs fail to capture transaction dependencies, leading to insufficient scheduling, high abort rates, and…
Many routing protocols have been proposed to handle reliability and real-time routing energy efficiency for wireless sensor networks. In this paper we propose a new routing protocol with QoS based capabilities for WSNs. We used priority…
A smart space offers entirely new opportunities for end users by adapting services accordingly to make life easy. A number of architectural designs have been proposed to design context awareness systems and adaptation behavior. However, the…
Emotion recognition from physiological signals has substantial potential for applications in mental health and emotion-aware systems. However, the lack of standardized, large-scale evaluations across heterogeneous datasets limits progress…
Integrating sensing into standardized communication systems can potentially benefit many consumer applications that require both radio frequency functions. However, without an effective sensing method, such integration may not achieve the…
Infrastructure sensing is vital for traffic monitoring at safety hotspots (e.g., intersections) and serves as the backbone of cooperative perception in autonomous driving. While vehicle sensing has been extensively studied, infrastructure…
The next generation wireless systems will face stringent new requirements, including ultra-low latency, high data rates and enhanced reliability. Large Intelligent Surfaces, is one proposed solution that has the potential to solve these…
Semantic Segmentation (SS) is promising for outdoor scene perception in safety-critical applications like autonomous vehicles, assisted navigation and so on. However, traditional SS is primarily based on RGB images, which limits the…
Live traffic analysis at the first aggregation point in the ISP network enables the implementation of complex traffic engineering policies but is limited by the scarce processing capabilities, especially for Deep Learning (DL) based…
The robust application of wireless sensor networks has increased during the past decade due to the potential use of wireless nodes in transmission of information by decreasing latency for surveillance and monitoring. The study proposes an…
The efficiency of current cargo screening processes at sea and air ports is largely unknown as few benchmarks exists against which they could be measured. Some manufacturers provide benchmarks for individual sensors but we found no…
Spectrum sensing is a key problem in cognitive radio. However, traditional detectors become ineffective when noise uncertainty is severe. It is shown that the entropy of Gauss white noise is constant in the frequency domain, and a robust…
This paper proposes a hardware-software co-design approach to efficiently optimize beamforming and port selection in fluid antenna systems (FASs). To begin with, a fluid-antenna (FA)-enabled downlink multi-cell multiple-input…
This paper explores the application of spiking neural networks (SNNs), known for their low-power binary spikes, to bearing fault diagnosis, bridging the gap between high-performance AI algorithms and real-world industrial scenarios. In…
In this manuscript, two novel multi-hop relay-assisted hybrid Free Space Optical / Radio Frequency (FSO / RF) communication systems are presented and compared. In these structures, RF and FSO links, at each hop, are parallel and send data…
In recent years, with the rapid development of sensing technology and the Internet of Things (IoT), sensors play increasingly important roles in traffic control, medical monitoring, industrial production and etc. They generated high volume…
Cognitive relaying has been introduced for opportunistic spectrum access systems by which a secondary node forwards primary packets whenever the primary link faces an outage condition. For spectrum sharing systems, cognitive relaying is…
LLM systems must make control decisions in addition to generating outputs: whether to answer, clarify, retrieve, call tools, repair, or escalate. In many current architectures, these decisions remain implicit within generation, entangling…
Few-Shot Semantic Segmentation (FSS) models achieve strong performance in segmenting novel classes with minimal labeled examples, yet their decision-making processes remain largely opaque. While explainable AI has advanced significantly in…
Federated machine learning is growing fast in academia and industries as a solution to solve data hungriness and privacy issues in machine learning. Being a widely distributed system, federated machine learning requires various system…