Respiratory diseases are major global killers, demanding early diagnosis for effective management. Digital stethoscopes offer promise, but face limitations in storage and transmission. A compressive sensing-based compression algorithm is needed to address these constraints. Meanwhile, fast-reconstruction CS algorithms are sought to balance speed and fidelity. Sound event detection algorithms are crucial for identifying abnormal lung sounds and augmenting diagnostic accuracy. Integrating these technologies can revolutionize respiratory disease management, enhancing patient outcomes.

Last Updated On: 
Mon, 04/08/2024 - 03:42

Globally, respiratory diseases are the leading cause of death, making it essential to develop an automatic respiratory sounds software to speed up diagnosis and reduce physician workload. A recent line of attempts have been proposed to predict accurately, but they have yet been able to provide a satisfactory generalization performance. In this contest, we invited the community to develop more accurate and generalized respiratory sound algorithms. A starter code is provided to standardize the submissions and lower the barrier.

Last Updated On: 
Mon, 04/01/2024 - 08:51

The dataset comprises diverse objects detectable by drones during aerial surveys, encapsulating an extensive array of environmental and man-made elements. Encompassing natural entities like trees, water bodies, terrain features, and vegetation, it also incorporates urban objects such as buildings, roads, vehicles, and infrastructure. The dataset delineates distinct categories, encompassing fine-grained details within each classification, catering to the nuances of aerial detection.


Sensor arrays are ubiquitous. They capture images in digital cameras, record the swipes of our fingers on the screens of our phones and tablets, or map pressure distribution over an area. Soft capacitive sensor arrays have been proposed to make electronic pressure-sensing skins capable of identifying the location and intensity of touch. However, large arrays of those sensors remain challenging to produce, as they require high-resolution patterning of electrodes and routing of long and thin electrical connections.


Abstract—A novel approach is proposed in this article to boost the energy efficiency (EE) of an AoI-aware IoT network. In particular, we propose a new approach that is based a combination of simultaneous wireless information and power


A new approach addressing the spectrum scarcity challenge in 6G networks by implementing an enhanced licensed shared access (LSA) framework is considered. The proposed mechanism aims to ensure fairness in spectrum allocation to mobile network operators (MNOs) through a novel weighted auction called the fair Vickery-Clarke-Groves (FVCG) mechanism in which the determination of weights is based on the results of the previous auctions.


In this paper, we develop a hierarchical aerial computing framework composed of high altitude platform (HAP) and unmanned aerial vehicles (UAVs) to compute the fully offloaded tasks of terrestrial mobile users which are connected through an uplink non-orthogonal multiple access (UL-NOMA).


In this paper, we propose a novel cooperative resource sharing in a multi-tier edge slicing networks which is

robust to imperfect channel state information (CSI) caused by user equipments’ (UEs) mobility. Due to the mobility

of UEs, the dynamic requirements of their tasks, and the limited resources of the network, we propose a smart joint

dynamic pricing and resources sharing (SJDPRS) scenario that can incentivize the infrastructure provider (InP) and

mobile network operators (MNOs). Aiming to maximize the profits of UEs, MNOs and the InP under the task


Abstract— Objective: Recently, pupil oscillation synchronized with a steady visual stimulus was employed for an input of an interface. The system is inspired by steady-state visual evoked potential (SSVEP) BCIs, but it eliminates the need for contact with the participant because it does not need electrodes to measure electroencephalography. However, the stimulation frequency is restricted to being below 2.5 Hz because of the mechanics of pupillary vibration and information transfer rate (ITR) is lower than SSVEP BCIs.


Abstract—Network slicing (NwS) is one of the main technologies

in the €…h-generation of mobile communication and

beyond (5G+). One of the important challenges in the NwS

is information uncertainty which mainly involves demand

and channel state information (CSI). Demand uncertainty is

divided into three types: number of users requests, amount

of bandwidth, and requested virtual network functions workloads.

Moreover, the CSI uncertainty is modeled by three

methods: worst-case, probabilistic, and hybrid. In this paper,