Few-Mode Fiber with Low Spontaneous Raman Scattering for Quantum Key Distribution and Classical Optical Communication Coexistence Systems.

In this paper, the theoretical model of spontaneous Raman scattering (SpRS) in few-mode fiber (FMF) is discussed. The influence of SpRS on quantum key distribution (QKD) in FMF is evaluated by combining wavelength division multiplexing (WDM) and space division multiplexing (SDM) techniques. On this basis, an improved ring-assisted FMF is designed and characterized; the transmission distance can be increased by up to 54.

Tactile-GAT: tactile graph attention networks for robot tactile perception classification.

As one of the most important senses in human beings, touch can also help robots better perceive and adapt to complex environmental information, improving their autonomous decision-making and execution capabilities. Compared to other perception methods, tactile perception needs to handle multi-channel tactile signals simultaneously, such as pressure, bending, temperature, and humidity. However, directly transferring deep learning algorithms that work well on temporal signals to tactile signal tasks does not effectively utilize the physical spatial connectivity information of tactile sensors.

Image tampering detection based on RDS-YOLOv5 feature enhancement transformation.

Malicious image tampering has gradually become another way to threaten social stability and personal safety. Timely detection and precise positioning can help reduce the occurrence of risks and improve the overall safety of society. Due to the limitations of highly targeted dataset training and low-level feature extraction efficiency, the generalization and actual performance of the recent tampered detection technology have not yet reached expectations.

Optimizing secure multimedia communication in embedded systems a parallel convolutional neural network approach to RIS and D2D resource allocation.

With the rapid development of Internet of Things (IoT) services, technologies that leverage multimedia computer communication for information sharing in embedded systems have become a research focus. To address the challenges of low spectral efficiency and poor network flexibility in multimedia computer communications, this paper proposes a resource allocation scheme based on parallel Convolutional Neural Network (CNN). The scheme optimizes the base station beamforming vector and the Reconfigurable Intelligent Surface (RIS) phase shifts to maximize the secure transmission rate for cellular users (CUs), while ensuring normal and secure communication for device-to-device (D2D) users.

Enhanced Coexistence of Quantum Key Distribution and Classical Communication over Hollow-Core and Multi-Core Fibers.

In this paper, we investigate the impact of classical optical communications in quantum key distribution (QKD) over hollow-core fiber (HCF), multi-core fiber (MCF) and single-core fiber (SCF) and propose wavelength allocation schemes to enhance QKD performance. Firstly, we theoretically analyze noise interference in QKD over HCF, MCF and SCF, such as spontaneous Raman scattering (SpRS) and four-wave mixing (FWM). To mitigate these noise types and optimize QKD performance, we propose a joint noise suppression wavelength allocation (JSWA) scheme.

Remanufacturing and channel strategies in e-commerce closed-loop supply chain.

This paper studies the recycling and remanufacturing mode and sales channel issues in the closed-loop supply chain. Specifically, this study establishes an e-commerce closed-loop supply chain consisting of a manufacturer and an e-commerce platform, and divides the recycling model into recycling by the manufacturer or recycling by the platform. Considering two common sales models in e-commerce platforms: the resale model and agency model, combined with the recycling model, four different research scenarios are formed.

Adaptable cascaded registration for personalized maxilla completion and cleft defect volume estimation.

Background: Cone-beam computed tomography (CBCT) images provide high-resolution insights into the underlying craniofacial anomaly in patients with cleft lip and palate (CLP), requiring non-negligible annotation costs to measure the cleft defect for the guidance of the clinical secondary alveolar bone graft procedures. Considering the cumbersome volumetric image acquisition, there is a lack of paired CLP CBCTs and normal CBCTs for learning-based anatomical structure restoration models. Nowadays, the registration-based method relieves the annotation burden, though one-shot registration and the regular mask are limited to handling fine-grained shape variations and harmony between restored bony tissues and the defected maxilla.

Attention Mechanism and LSTM Network for Fingerprint-Based Indoor Location System.

The demand for precise indoor localization services is steadily increasing. Among various methods, fingerprint-based indoor localization has become a popular choice due to its exceptional accuracy, cost-effectiveness, and ease of implementation. However, its performance degrades significantly as a result of multipath signal attenuation and environmental changes.

Core network traffic prediction based on vertical federated learning and split learning.

Wireless traffic prediction is vital for intelligent cellular network operations, such as load-aware resource management and predictive control. Traditional centralized training addresses this but poses issues like excessive data transmission, disregarding delays, and user privacy. Traditional federated learning methods can meet the requirement of jointly training models while protecting the privacy of all parties' data.

Multi-Classification and Tree-Based Ensemble Network for the Intrusion Detection System in the Internet of Vehicles.

The Internet of Vehicles(IoV) employs vehicle-to-everything (V2X) technology to establish intricate interconnections among the Internet, the IoT network, and the Vehicle Networks (IVNs), forming a complex vehicle communication network. However, the vehicle communication network is very vulnerable to attacks. The implementation of an intrusion detection system (IDS) emerges as an essential requisite to ensure the security of in-vehicle/inter-vehicle communication in IoV.

Multi-UAV Data Collection and Path Planning Method for Large-Scale Terminal Access.

In the context of the relentless evolution of network and communication technologies, the need for enhanced communication content and quality continues to escalate. Addressing the demands of data collection from the abundance of terminals within Internet of Things (IoT) scenarios, this paper presents an advanced approach to multi-Unmanned Aerial Vehicle (UAV) data collection and path planning tailored for extensive terminal accessibility. This paper focuses on optimizing the complex interplay between task completion time and task volume equilibrium.

A multi-dimensional fusion strategy similarity measure method for patent application technology disclosure document.

Patent application technology disclosure document is one of the important bases for judging patent novelty and uniqueness. Automated evaluation can effectively solve the problems of long time and strong subjectivity of human evaluation. The text similarity evaluation algorithm based on corpus and deep learning technology has problems such as insufficient amount of cross-library learning data and insufficient core content tendency in the similarity judgment of patent application technology disclosure document, which limits their performance and practical application.

Resource Allocation for Cognitive LEO Satellite Systems: Facilitating IoT Communications.

Due to the characteristics of global coverage, on-demand access, and large capacity, the low earth orbit (LEO) satellite communication (SatCom) has become one promising technology to support the Internet-of-Things (IoT). However, due to the scarcity of satellite spectrum and the high cost of designing satellites, it is difficult to launch a dedicated satellite for IoT communications. To facilitate IoT communications over LEO SatCom, in this paper, we propose the cognitive LEO satellite system, where the IoT users act as the secondary user to access the legacy LEO satellites and cognitively use the spectrum of the legacy LEO users.

The value evaluation model design and business innovation for P-RAN based on multi-party interaction.

This paper takes the P-RAN, a proximity wireless access network system for 5G and 6G, as an example, and uses the theory related to value evaluation to discuss how to realize the decentralization of underlying infrastructure from the perspective of different interactive players in the system. The analysis of P-RAN helps to promote mobile network operators to recognize network interaction and solve the problems of weak coverage, reduce the cost of network construction, and provides a new research idea for exploring more network evaluation indicators in the future.

Federated learning with hyper-network-a case study on whole slide image analysis.

Federated learning(FL) is a new kind of Artificial Intelligence(AI) aimed at data privacy preservation that builds on decentralizing the training data for the deep learning model. This new technique of data security and privacy sheds light on many critical domains with highly sensitive data, including medical image analysis. Developing a strong, scalable, and precise deep learning model has proven to count on a variety of high-quality data from different centers.

Blockchained supply chain management based on IoT tracking and machine learning.

When it comes to running and managing modern supply chains, 6G Internet of things (IoT) is of utmost importance. To provide IoT with security and automation, blockchain and machine learning are two upper-layer technology that can help. First, we propose to utilize blockchain in modern supply chains to ensure efficient collaboration between all parties.

Device-Free Multi-Location Human Activity Recognition Using Deep Complex Network.

Wi-Fi-based human activity recognition has attracted broad attention for its advantages, which include being device-free, privacy-protected, unaffected by light, etc. Owing to the development of artificial intelligence techniques, existing methods have made great improvements in sensing accuracy. However, the performance of multi-location recognition is still a challenging issue.

Development of Wireless Network Indoor Coverage System Based on Optical Fiber Distribution System.

With the continuous development of network communication technology, the domestic network has covered the homes of ordinary people, but the indoor coverage system of the network cable network needs to be further improved. The optical fiber distribution system is a signal coverage system integrating GSM, TD-SCDMA, and other standards. It is mainly composed of system access unit, system expansion unit, and system remote unit.