Network Communication Technology Research Articles

Aspiring and Deprecating Female Influencers: Communicative Capitalism and the Positioning of Women Entrepreneurs

Given the relative ease of joining an e-commerce market via social media platforms, expectations have risen about the role of communication technology and social networks in advancing gender equality in economic participation. South Korean women influencers, in particular, are selling various items using their popularity on social networks. They represent themselves as successful, passionate, gorgeous businesswomen with glamorous lifestyles. These individual influencers exemplify neoliberal ideals, branding and marketing themselves as independent and autonomous creators able to fashion their own destinies in the endless competition of the market. Recently however, heated deinfluencing trends against them have grown in strength and intensity, deprecating these women as nonprofessional, mass-deceptive online vendors. It has become common to describe them with the derogatory term “palyi people.” Against this backdrop, the current study questions the ability of digitalized online technology to empower women coming along with the ideas of neoliberalism and postfeminism. Using the concept of communicative capitalism, this study will analyze the images and texts created and circulated within the social media sphere by six popular female influencers and their followers. Through this data, this study aims to grasp how the free communicative activities of female influencers and their followers on social media negatively position women entrepreneurs in the techno-cultural era.

Start Time Planning for Cyclic Queuing and Forwarding in Time-Sensitive Networks

Time-sensitive networking (TSN) is a kind of network communication technology applied in fields such as industrial internet and intelligent transportation, capable of meeting the application requirements for precise time synchronization and low-latency deterministic forwarding. In TSN, cyclic queuing and forwarding (CQF) is a traffic shaping mechanism that has been extensively discussed in the recent literature, which allows the delay of time-triggered (TT) flow to be definite and easily calculable. In this paper, two algorithms are designed to tackle the start time planning issue with the CQF mechanism, namely the flow–path–offset joint scheduling (FPOJS) algorithm and congestion-aware scheduling algorithm, to improve the scheduling success ratio of TT flows. The FPOJS algorithm, which adopts a novel scheduling object—a combination of flow, path, and offset—implements scheduling in descending order of a well-designed priority that considers the resource capacity and resource requirements of ports. The congestion-aware scheduling algorithm identifies and optimizes congested ports during scheduling and substantially improves the scheduling success ratio by dynamically configuring port resources. The experimental results demonstrate that the FPOJS algorithm achieves a 39% improvement in the scheduling success ratio over the naive algorithm, 13% over the Tabu-ITP algorithm, and 10% over the MSS algorithm. Moreover, the algorithm exhibits a higher scheduling success ratio under large-scale TSN.

Instagram vixens: the racialized sexual scripts of erotic labor online

ABSTRACT Despite growing interest in the ways information and communication technologies shape labor, few studies have accounted for the racialized sexualization of erotic labor. This study examines how Black women exotic dancers deploy racialized sexual scripts in the content they generate on the mobile social networking application Instagram. As erotic influencers, these women engage in multifaceted and multimodal erotic self-presentations both within and beyond the strip club. This article presents data from a digital ethnography of 73 Black female exotic dancers located in the southeastern United States, as well as a content analysis of the digital media files they created on Instagram. The findings suggest four distinct sexual scripts that these Instagram users perform: virtual cover girl, erotic professional, boudoir baddie, and assets model. Findings demonstrate Black women use smartphone and social networking technological features to create presentations of femininity, desirability, and sensuality that simultaneously subvert and adhere to the controlling images that define Western ideologies on race and sexuality. Ultimately, this article argues for the need to account for the social and cultural contexts in which the affordances of networked communication technologies that permeate contemporary erotic labor operate.

Implementación de un Dispositivo Inteligente para la Asistencia de Personas con Discapacidad Visual en Entornos Universitarios

This project arises in response to the growing global need for inclusive technological solutions aimed at improving the quality of life of people with visual impairments. The motivation is based on addressing the specific barriers these individuals face, with a particular focus on university environments. The methodology adopted focuses on the convergence of web services and networked communication technologies, seeking to promote the autonomy and safety of visually impaired people. A distinctive aspect of this project is the implementation of low power consumption and long-range technology, marking a pioneering approach in this field, which not only addresses the immediate need for inclusive solutions; but contributes to technological advancement by introducing efficient and long-range solutions. Through testing, very short response times are achieved in terms of identifying dangerous movements such as falls and detecting nearby objects, while character recognition still requires further refinement. The key innovation lies in the effective convergence of technologies, setting a new standard for inclusive and sustainable solutions. In other words, this project not only responds to a pressing need, but also marks a significant milestone in improving inclusion for the visually impaired, highlighting its relevance at the local level and contributing to global progress in this crucial field.

Cutting-Edge Challenges in Communication Technology and Computer Network Security

The rapid development of communication technology and computer networks has brought a lot of convenience to production and life, but it also increases the security problem. Information security has become one of the severe challenges faced by people in the digital age. Currently, the security problems facing the field of communication technology and computer networks in China mainly include the evolution of offensive technology, the risk of large-scale data transmission, the potential vulnerabilities introduced by emerging technology, and the dilemma of user identity verification. This paper analyzes the frontier challenges of communication technology and computer network security, and puts forward corresponding solutions, hoping to provide ideas for coping with the security challenges of communication technology and computer networks.

Multi-Path Data Transmission System Based on 5G Communication Technology

Due to the current problems of 5G(5th Generation Mobile Communication Technology) networks such as discontinuous coverage, poor coverage performance, and insufficient uplink rate, the real-time transmission performance of 5G networks has been greatly affected, and cannot meet the growing needs of high-speed communication and applications based on the Internet of Things. This paper aims to improve the transmission effect of 5G communication technology by improving the algorithm. By analyzing the problems of existing 5G bandwidth estimation algorithm, this paper proposes a Westwood-based coupling adaptive bandwidth estimation algorithm, and describes the algorithm ideas involved in the algorithm point-by-point. Moreover, this paper uses adaptive bandwidth estimation algorithm to update the slow start threshold in the fast retransmission phase, which makes the congestion window size of path transmission more reasonable. Simulation results show that the congestion control algorithm proposed in this paper improves the accuracy of link bandwidth estimation to a certain extent, improves the link congestion situation and improves the throughput of multipath transmission links. This article can be applied to the algorithm in multipath data transmission to further improve data processing efficiency and processing speed.Therefore, the improved method in this paper can be used in the practice of 5G communication to further improve the efficiency of 5G communication.

IRS-assisted UAV wireless powered communication network for sustainable federated learning

Intelligent reflective surface (IRS) and unmanned aerial vehicle (UAV) communication are indispensable potential technologies in the future sixth-generation mobile communication technology (6 G). Utilizing the high beamforming gain of IRS and the high mobility of UAV can achieve ubiquitous network coverage and ensure a high-quality communication environment. Wireless Powered Communication Network (WPCN) is an emerging green communication technology network that converts received radio frequency (RF) signals into electrical energy to power Federated Learning (FL) users. FL users perform local computing and model transmission through the collected energy, ensuring the sustainability of FL. In order to solve the problems of complex communication environment, privacy protection, and energy constraints on terminal devices, we design an FL system based on an IRS-assisted UAV wireless power communication network, which minimizes the UAV transmission energy by jointly optimizing UAV location, IRS phase shift, and resource allocation strategies. We use a low-complexity iterative algorithm to solve this complex non-convex problem. The simulation results show that the performance of the proposed algorithm is obviously better than that of other benchmark schemes, indicating that joint optimization plays an essential role in improving the performance of the system.

Long-distance Tele-robotic-assisted Percutaneous Coronary Intervention: A Case Report of First-in-patient in China

Robotic-assisted percutaneous coronary intervention (R-PCI) is an innovative way of performing percutaneous coronary intervention (PCI) whereby the operator can manipulate coronary intraluminal guidewires and catheter devices by using remotely controlled technology. Performing tele-R-PCI from a remote location via fifth generation network communication technology has never been reported in China; however, if this were possible, the technique could be used to treat many patients with coronary artery disease who would otherwise not have the opportunity of treatment. The case of a 73-year-old male patient with coronary artery disease who underwent successful tele-R-PCI at 800 km from the operators is presented. Performing long-distance tele-R-PCI in patients with coronary artery disease is feasible with predictably successful outcomes when reliable network connectivity and local cardiac catheterization facilities are present.

Prediction of novel malware using hybrid convolution neural network and long short-term memory approach

The rapid evolution of network communication technologies has led to the emergence of new forms of malware and cybercrimes, posing significant threats to user safety, network infrastructure integrity, and data privacy. Despite efforts to develop advanced algorithms for detecting malicious activity, constructing models that are both accurate and reliable remains a challenge, especially in handling vast and dynamically shifting data patterns. The prevalent bag-of-words (BOW) method, while widely used, falls short in capturing crucial spatial and sequence information vital for detecting malware patterns. To address this challenge, the work presented in this paper proposes hybrid convolution neural network-long short-term memory network (CNN-LSTM) combination models, leveraging CNN's spatial information extraction and LSTM's temporal modeling capabilities. Focused on predicting the infiltration of malicious software into personal computers, the proposed hybrid CNN-LSTM model considers factors such as location, firmware version, operating system, and anti-virus software. The proposed models undergo training and evaluation using Microsoft's malware dataset, demonstrating superior performance compared to traditional CNN and LSTM models. The CNN-LSTM model achieves an impressive accuracy of 95% on the Microsoft malware dataset, highlighting its effectiveness in malware detection.

Sailing into the future: technologies, challenges, and opportunities for maritime communication networks in the 6G era

The maritime domain is a major driver of economic growth with emerging services, comprising intelligent transportation systems (ITSs), smart ports, security and safety, and ocean monitoring systems. Sixth generation (6G) mobile networks will offer various technologies, paving the way for reliable and autonomous maritime communication networks (MCNs), supporting these novel maritime services. This review presents the main enabling technologies for future MCNs and relevant use cases, including ITSs with reduced carbon footprint, ports and maritime infrastructure security, as well as fault detection and predictive maintenance. Moreover, the current trends in integrated satellite-aerial-terrestrial-maritime network architectures are discussed together with the different network segments and communication technologies, and machine learning integration aspects.

Data Communication Over Power-lines: A Review on Technical, and Applications Challenges

This paper presents a review study on the data communication over power-lines, commonly referred to as power-line carrier, power-line communication (PLC), mains communications, or power-line digital subscriber line (PDSL). This study examines the technical and application advantages and challenges associated with adopting PLC as a preferred alternative technology for wideband or broadband data communication. The broader coverage area of the PLC network gives it a distinct advantage over other communication network technologies. Additionally, implementing a communication system using the existing power-line network is more cost-effective and less time-consuming compared to constructing a new network from scratch. However, the primary challenge lies in the fact that the power-line network is primarily designed for the distribution of electrical power within the frequency range of 50-60 Hz including the harmonics. This poses various obstacles such as electrical noise from appliances, signal distortions caused by the unregulated nature of the wiring, transformer bypassing, interference from high-frequency modulation, and variations in characteristic impedances, among others. Despite these challenges, the emergence of robust modulation techniques like Orthogonal Frequency Division Multiplexing (OFDM) and Direct-Sequence Spread Spectrum (DSSS), along with the development of Application-Specific Integrated Circuit (ASIC) density with improved processing speeds, as well as advancements in signal processing and error control coding techniques, have made the PLC network the most promising telecommunications access network.

Application of artificial bee colony algorithm based on homogenization mapping and collaborative acquisition control in network communication security.

In order to optimize the spectrum allocation strategy of existing wireless communication networks and improve information transmission efficiency and data transmission security, this study uses the independent correlation characteristics of chaotic time series to simulate the collection and control strategy of bees, and proposes an artificial bee colony algorithm based on uniform mapping and collaborative collection control. Furthermore, it proposes an artificial bee colony algorithm based on uniform mapping and collaborative collection and control. The method begins by establishing a composite system of uniformly distributed Chebyshev maps. In the neighborhood intervals where the nectar sources are firmly connected and relatively independent, the algorithm then conducts a chaotic traversal search. The research results demonstrated the great performance of the suggested algorithm in each test function as well as the positive effects of the optimization search. The network throughput rate was over 300 kbps, the quantity of security service eavesdropping was below 0.1, and the spectrum utilization rate of the algorithm-based allocation method could be enhanced to 0.8 at the most. Overall, the performance of the proposed algorithm outperformed the comparison algorithm, with high optimization accuracy and a significant amount of optimization. This is favorable for the efficient use of spectrum resources and the secure transmission of communication data, and it encourages the development of spectrum allocation technology in wireless communication networks.

Research on a Vehicle-Mounted Emergency Communication System Using BeiDou Regional Short Message Communication (RSMC) for Firefighting Operations in Forest Areas without a Public Network

The low coverage of public networks in pristine forest areas prevents on-site firefighters from communicating directly with remote command centers during forest fires, reducing firefighting efficiency. In this study, we designed a vehicle-mounted emergency communication system Using BeiDou RSMC (Regional Short Message Communication) for firefighting operations in forest areas without a public network to establish a satellite communication network and Zigbee self-organizing network technology to establish a local self-organizing network. Beidou RSMC is a satellite communication service developed and operated independently by China, and its signals now cover the entire globe. The combination of these two components ensures emergency communication in the event of a fire in a forest area without public network coverage. The performance of the system was tested by simulating a fire, and it was able to establish a reliable communication link between the firefighters on the scene and the remote command center in the absence of a public network. The proposed system solves the emergency communication problem that arises when a fire occurs in a forest area without a public network, enabling the remote command center to monitor fire information and dispatch various resources in real time, thereby improving firefighting efficiency and reducing casualties.

Design and performance analysis of L‐slotted MIMO antenna with improved isolation using defected ground structure for S‐band satellite application

SummaryThe increasing prevalence of MIMO technology in wireless communication networks is attributed to its ability to augment system capacity and dependability. Consequently, there is a notable enthusiasm for the advancement and implementation of S‐band applications. Nevertheless, the mutual coupling between numerous antennas presents a crucial obstacle to MIMO system performance. This paper presents a novel technique that utilizes a defective ground structure with parasitic components to increase antenna isolation and gain. Additionally, an L‐shaped slot is incorporated into the patch element to enhance the antennas impedance bandwidth. Antennas are intentionally placed in a perpendicular arrangement to minimize the impact of the coupling effects. The antenna exhibits an impedance bandwidth in the frequency range of 2.62–2.79 GHz. Furthermore, the utilization of a four‐element MIMO antenna setup with a defective ground structure yields outstanding isolation properties, with values notably lower than −25 dB. To achieve an optimal MIMO performance, we assessed various diversity parameters, including diversity gain, channel capacity loss, total active reflection coefficient, and envelope correlation coefficient. The parameter values were within acceptable limits (ECC < 0.04, DG = 10 dB, TARC < 0 dB, and CCL < 0.1 bits/s/Hz). This research paper therefore offers essential insights into the design and optimization of MIMO antennas specifically for 2.7 GHz applications.

A stable satellite routing algorithm based on a-star algorithm in dynamic networks

Abstract This paper focuses on solving the routing optimization problem under the dynamic topology of the satellite communication network. With the rapid development of low-earth-orbit (LEO) satellite network communication technology, the dynamically changing topology of satellite networks has brought about frequent link switching and triggered a large number of routing updates. This paper proposes an improved routing algorithm named the Stable A-Star Routing (SASR) algorithm. The SASR algorithm is based on the A-star algorithm and aims to reduce path-switching frequency and enhance path stability by optimizing the path selection strategy. Through detailed simulation experiments and performance evaluation, we verified the performance advantages of the SASR algorithm in terms of the number of path switches, the number of path hops, the route convergence time, and the occurrences of congestion in business under different business volumes, and conducted comparative studies with classic algorithms. The results show that the SASR algorithm offers obvious advantages in key performance indicators. Compared with the Dijkstra algorithm and the A-star algorithm, the average number of path switches can be reduced by 22% and 10%, respectively. It shows more prominent advantages under a larger business volume, providing an efficient and reliable solution for routing optimization under the dynamic topology of satellite communication networks.

Performance of Smart Grid Based on Data Aggregation Using Wireless Communication Network Technology

With the advancements in technology, electrical energy has become a basic need to support every field of life including Electric Vehicles (EVs), Industry automation, security networks and communication systems. This, in turn, demands a high order of design, protection and measurement setup of power transmission from the energy source to the end users (load) with minimum loss of energy. All types of loads need a nominal supply voltage to operate, which necessary for its safe operation. Usually the nominal-rated voltage allows ±5% variation tolerance in the operation of loads, without affecting the equipment. The transmission lines that connect several smart grids are called as interconnection, by using it the stability and proficiency can be increased. It should provide reliable and secure communication, with a low-cost solution. Hence, in this research paper, an efficient communication system based on wireless sensor networks will be under consideration, to ensure good quality of service for smart grids. The initial two points that are required to be covered include 1) research on optimum network topology to connect several smart grids and 2) interference cancellation to avoid errors in transmission due to the induced field from the power lines. In addition, 3) the wireless sensor network will be used to support efficient data collection, self-organization of the network and data reduction by removing the redundancy. Finally, 4) development of data prediction algorithm to reduce the transmission rate and latency. Overall, these approaches will help in development of smart network to reduce the energy wastage, ensure nominal supply voltage, increased reliability and improved communication network as compared to existing solutions. The presented work includes the two sorts of wind and solar energy in ordinary working environments and illuminates the energy trade between buyers and power Production Company. The expense of power isn't thought about; however, the various buyers can pick the least expensive energy.

Construction of neural network model for exercise load monitoring based on yoga training data and rehabilitation therapy

The Internet of Things is based on the traditional Internet and its purpose is to achieve information exchange between users and devices, as well as between devices. The rapid development of sensor technology, communication network technology, and computer technology has enriched the coverage of the Internet of Things, including a wide range of intelligent applications such as healthcare, smart cities, and smart homes. The development of high-performance computing and machine learning technologies has promoted the wide application of intelligent auxiliary systems in sports medicine. With the rapid development of yoga in the field of sports, athletes can play the various functions of yoga, improve their physical strength and quality, and improve their strength, flexibility, etc., cultivate positive, optimistic, and healthy emotions, and these are conducive to rehabilitation treatment after sports injuries. Therefore, it is feasible and feasible to introduce yoga training into the monitoring of the exercise load of athletes. In this paper, neural network technology was used to break the traditional training method based on experience. Based on yoga training data, through experimental exercise research, it could explore a new effective way to monitor exercise load and rehabilitation treatment, and build an exercise load monitoring model of the Ant Colony Optimization (ACO) neural network. By sorting out the data, statistics and analysis of the data, this article confirmed the effect of yoga training on reducing fatigue after exercise. The experimental results showed that the prediction value obtained by the ACO neural network model was 9.106, and the error was only −0.003 compared to the actual detection value of 9.109. This result showed that the ACO neural network model can perfectly fit the functional relationship between yoga training level and exercise load and has high prediction accuracy. This also marked that the development of high-performance computing systems has entered a new journey in the field of sports and health.

Object–attribute–relation model-based semantic coding for image transmission

The development of digital, networked and intelligent communication technology has led to significant growth in data and services. Especially in the communication scenario of monitoring data, a variety of downstream tasks bring significant technical challenges for high-performance data transmission, information mining, and data distribution. The problem to be solved is the coding and low bit-rate transmission of large amounts of surveillance data. Concepts and methods that utilize semantic communication are needed. This paper proposes a communication architecture based on the object–attribute–relation (OAR) semantic knowledge base. The sender uses the model parameters and prior knowledge in the knowledge base to drive the OAR extraction model to encode the image. After semantic coding and channel coding, the signal is transmitted to the receiver through the physical channel. At the receiver, the signal is decoded into a semantic vector. The OAR global vector is generated by structured processing, which is used for downstream tasks such as image retrieval or image reconstruction. Experimental comparison and analysis illustrate the effectiveness and superiority of each part of the communication framework. This approach provides a new solution for improving data utilization and processing efficiency.

Automated deployment mechanism of containerized communication micro-services for smart manufacturing applications

To swiftly and reliably monitor various information and the operational status of machinery across large smart manufacturing sites, this study introduces the use of LPWAN multi-mode network communication technology. This technology can automatically switch between LoRa and NB-IoT modes based on signal strength to ensure communication stability. Through wireless communication technologies such as LoRa and NB-IoT, the status information of machinery can be transmitted back to the cloud in real-time, facilitating user management. However, LPWAN multi-mode network communication modules often adopt a monolithic architecture, making maintenance and upgrades more difficult. When an application within the module needs upgrading, not only must the consistency between the development environment and the execution environment be ensured, but also a significant amount of time and resources must be spent on on-site deployment. With the development of cloud computing and virtualization technologies, containerized microservices architecture, which focuses on replacing functional modules with services, is set to become the mainstream for future industrial applications. Therefore, this study proposes a remote communication architecture based on container and microservices technologies. Utilizing the concept of microservices, this architecture divides LPWAN multi-mode network communication modules based on different functionalities and offers them to users in a more flexible service manner through containerization technology. This study also designs a mechanism to automate the entire service construction process, followed by the implementation of communication services’ automatic deployment through container management tools. Compared to manual deployment, this significantly reduces the waste of time and human resources. Finally, this study uses a large mobile pumping unit as a practical application case to verify the feasibility of the proposed architecture. In the context of flood prevention and disaster relief, large mobile pumping units are widely used to solve flooding issues. These pumps are often deployed in dangerous areas with poor signal reception, thereby also validating the value of the proposed architecture.

Symmetric Collaborative Fault-Tolerant Control of Multi-Intelligence under Long-Range Transmission in Air–Ground Integrated Wireless High-Mobility Self-Organizing Networks

With the continuous development and progress of wireless self-organizing network communication technology, how to carry out long-distance cooperative control of multiple intelligences under the framework of an air–ground integrated wireless high-mobility self-organizing network has become a hot and difficult topic that needs to be solved urgently. This paper takes the air–ground integrated wireless high-mobility self-organizing network system as the basic framework and focuses on solving the long-distance cooperative fault-tolerant control of multi-intelligent bodies and the topological stability of a wireless mobile self-organizing network. To solve the above problems, a direct neural network with a robust adaptive fault-tolerant controller is designed in this paper. By constructing a symmetric population neural network model and combining it with the Lyapunov stabilization criterion, the system feedback matrix K has the ability of autonomous adaptive learning, and symmetrically distorts, rotates, or scales the training data to instantly adjust the system’s fault-tolerant corrections and adaptive adjusting factors to resist the unknown disturbances and faults, to achieve the goals of multi-intelligent body stable control and the stable operation of a wireless high-mobility self-organizing network topology. Simulation results show that with the feedback adjustment of the multi-system under the designed controller, the multi-system as a whole has good fault-tolerant performance and autonomous learning approximation performance, and the tracking error asymptotically converges to zero. The experimental results show that the multi-flight subsystems fly stably, the air–ground integrated wireless high-mobility self-organizing network topology has good stability performance, and the maximum relative improvement of the topology stability performance is 50%.