Low-power ambient backscatter communication (AmBC) relying on radio-frequency (RF) energy harvesting is an energy-efficient solution for batteryless Internet of Things (IoT). However, ambient backscatter signals are severely faded by dyadic backscatt...
Deep Reinforcement Learning (DRL) has demonstrated promising capabilities for routing optimization in Software-Defined Networks (SDNs). However, existing DRL-based routing algorithms are struggling to extract graph-structured information and constrai...
Massive multiple-input multiple-output (MIMO) is a backbone technology in the fifth-generation (5G) and beyond 5G (B5G) networks. It enhances performance gain, energy efficiency, and spectral efficiency. Unfortunately, a massive number of antennas ne...
The hotspot issue in wireless sensor networks, with nodes nearest the sink node losing energy fastest and degrading network lifetime, is a well-referenced problem. Mobile sink nodes have been proposed as a solution to this. They do not completely rem...
Maritime heterogeneous wireless networks are characterized by dynamic topology and significant heterogeneity in bandwidth, latency, and coverage across communication paradigms, rendering traditional terrestrial routing protocols inadequate. To addres...
Metaheuristic and exact methods are one of the most common tools to solve Mixed-Integer Optimization Problems (MIPs). Most of these problems are NP-hard problems, being intractable to obtain optimal solutions in a reasonable time when the size of the...
In this study, a microscopic model for a swarm of mobile robots is developed to implement self-organized aggregation behavior. The proposed model relies on the concept of subjective expectation, which is defined as the “minimum wished cluster s...
In emergent technologies, data integrity is critical for message-passing communications, where security measures and validations must be considered to prevent the entrance of invalid data, detect errors in transmissions, and prevent data loss. The SH...
This paper presents a parallel implementation of a non-local transform-domain filter (BM4D). The effectiveness of the parallel implementation is demonstrated by denoising image series from computed tomography (CT) and magnetic resonance imaging (MRI)...
The application of single chain mean-field theory (SCMFT) on semiflexible chain brushes is reviewed. The worm-like chain (WLC) model is the best mode of semiflexible chain that can continuously recover to the rigid rod model and Gaussian chain (GC) m...
Monitoring the thermal behavior of distributed energy resources (DERs) network explores the dualism between thermal effects and electrical power flow. This paper proposes a design concept that monitors thermal conditions of DER grids, using ZigBee/GS...
The discovery and development of new drugs are extremely long and costly processes. Recent progress in artificial intelligence has made a positive impact on the drug development pipeline. Numerous challenges have been addressed with the growing explo...
Wireless multimedia sensor networks (WMSNs) have stringent constraints and need to deliver data packets to the sink node within a predefined limited time. However, due to congestion, buffer overflow occurs and leads to the degradation of the quality-...
Non-orthogonal multiple access (NOMA) has emerged as a promising technology that allows for multiplexing several users over limited time-frequency resources. Among existing NOMA methods, sparse code multiple access (SCMA) is especially attractive; no...
High-performance computing (HPC) and its supercomputers are essential for solving the most difficult issues in many scientific computing domains. The proliferation of computational resources utilized by HPC systems has resulted in an increase in the...
Effective noise reduction and speech enhancement algorithms have great potential to enhance lives of hearing aid users by restoring speech intelligibility. An open problem in today’s commercial hearing aids is how to take into account users’ preferen...
In this paper, we propose a novel deep learning-based framework for the joint design and decoding of linear block codes, the end-to-end deep coding cross-attention message-passing Transformer (E2E DC-CrossMPT). To improve linear block code design and...
The finite-difference time-domain (FDTD) method is a versatile electromagnetic simulation technique, widely used for solving various broadband problems. However, when dealing with complex structures and large dimensions, especially when applying perf...
The matrix information geometric signal detection (MIGSD) method has achieved satisfactory performance in many contexts of signal processing. However, this method involves many matrix exponential, logarithmic, and inverse operations, which result in...
Modern communication systems increasingly leverage multiple information streams—including channel observations, statistical models, and contextual knowledge—to enhance decoding reliability. However, the varying and often unpredictable qua...
In Orthogonal Time–Frequency Space (OTFS) systems, signal detection algorithms based on convolutional neural networks (CNNs) suffer from insufficient feature extraction and are limited by local mixing. Additionally, fixed convolution kernels st...
Considering the worst-case scenario, the junction-tree algorithm remains the most general solution for exact MAP inference with polynomial run-time guarantees. Unfortunately, its main tractability assumption requires the treewidth of a corresponding...
The binding of small organic molecules to protein targets is fundamental to a wide array of cellular functions. It is also routinely exploited to develop new therapeutic strategies against a variety of diseases. On that account, the ability to effect...
Partial discharge pattern recognition is a crucial task for assessing the insulation condition of Gas-Insulated Switchgear (GIS). However, the on-site environment presents challenges such as strong electromagnetic interference, leading to acquired si...
Nowadays, the research on vehicular computing enhanced a very huge amount of services and protocols, aimed to vehicles security and comfort. The investigation of the IEEE802.11p, Wireless Access in Vehicular Environments (WAVE) and Dedicated Short Ra...
13 November 2022
Molecular property prediction is essential for drug screening and reducing the cost of drug discovery. Current approaches combined with deep learning for drug prediction have proven their viability. Based on the previous deep learning networks, we pr...
Due to the complex topological relationship, poor data locality, and data racing problems in unstructured CFD computing, how to parallelize the finite volume method algorithms in shared memory to efficiently explore the hardware capabilities of many-...
Data association for space-based radar multi-target tracking is a significant challenge in dense clutter and complex scenarios, often leading to tracking errors and target loss. This paper proposes a classification-aided message-passing algorithm for...
In the recent past, Distributed Denial of Service (DDoS) attacks have become more abundant and present one of the most serious security threats. In a DDoS attack, the attacker controls a botnet of daemons residing in vulnerable hosts that send a sign...
Amidst the escalating need for stable power supplies and high-quality communication services in remote regions globally, due to challenges associated with deploying a conventional power communication infrastructure and its susceptibility to natural d...
The development of big data analytics in healthcare has created a demand for privacy-conscious and scalable machine learning algorithms that can allow the use of patient information across different healthcare organizations. In this study, the diffic...
In high-mobility communication scenarios, leveraging reconfigurable intelligent surfaces (RISs) to assist orthogonal time frequency space (OTFS) systems proves advantageous. Nevertheless, the integration of RIS into OTFS systems increases the complex...
Millimeter-wave (mmWave) MIMO systems have emerged as a key enabling technology for next-generation wireless networks, addressing the growing demand for ultra-high data rates through the utilization of wide bandwidths and large-scale antenna configur...
Large multi-UAV mission systems operate over time-varying communication graphs with heterogeneous platforms, where classical distributed task assignment may incur excessive message passing and suboptimal task–resource matching. To address these...
Over the past few years, there has been a surge in research attention towards tasks involving graph data, largely due to the impressive performance demonstrated by graph neural networks (GNNs) in handling such information. Currently, out-of-distribut...
Human–object interaction (HOI) detection is important for promoting the development of many fields such as human–computer interactions, service robotics, and video security surveillance. A high percentage of human–object pairs with...
Motion-compensated image reconstruction enables new clinical applications of Magnetic Resonance Imaging (MRI), but it relies on computationally intensive algorithms. This study focuses on the Generalized Reconstruction by Inversion of Coupled Systems...
Ultra-Wideband (UWB) positioning is a promising technique for underground mine localization, but its accuracy is strongly affected by complex tunnel topology, multipath propagation, and non-line-of-sight (NLOS) ranging errors. To address these challe...
This paper develops a reliability-oriented resource-allocation framework for a single-cell uplink sparse code multiple access (SCMA) system with fixed low-projection codebook (LPCB) constellation components. Link-level SCMA–message-passing-algo...
Online social networks are vital environments for information sharing and user interactivity. To help users of online social services to build, expand, and maintain their friend networks or webs of trust, trust management systems have been deployed a...
For direction-of-arrival (DOA) estimation problems in a sparse domain, sparse Bayesian learning (SBL) is highly favored by researchers owing to its excellent estimation performance. However, traditional SBL-based methods always assign Gaussian priors...
In this paper, we propose a novel family of semi-implicit hybrid finite volume/finite element schemes for computational fluid dynamics (CFD), in particular for the approximate solution of the incompressible and compressible Navier-Stokes equations, a...
With the development of mature Computational Fluid Dynamics (CFD) tools for fluids (air and liquid) and Finite Element Methods (FEM) for solids and structures, many approaches have been proposed to tackle the so-called Fluid–Structure Interaction or...
The discovery and advances of medicines may be considered as the ultimate relevant translational science effort that adds to human invulnerability and happiness. But advancing a fresh medication is a quite convoluted, costly, and protracted operation...
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