Traditional Communication Research Articles

Examining the Viability of AI-Generated Content in Revolutionizing China's News and Communication Industry: A Case Study of Xinhua News Agency

In recent years, artificial intelligence(AI for short)technology has continuously emerged and empowered various fields such as medical finance and e-commerce live broadcasting, but the development of enabling news and communication industry is currently lacking in discussion and attempts. This paper uses Xinhua News Agency as a case study and employs comparative and feasibility analysis methods to explore the challenges encountered during the digital transformation of the traditional news communication industry. It assesses the potential of AI-generated content (AIGC) to tackle these challenges, demonstrating AI's ability to enhance audience reach, improve content accuracy, and personalize news delivery. By examining the intrinsic connection between AI-generated content technology and the news communication process, this study underscores AI's pivotal role in driving unique digital transformation within the traditional news communication sector. Nevertheless, the paper acknowledges the current insufficiency of data supporting Xinhua News Agency's AI news production. Future research should prioritize the collection and analysis of case data to facilitate a more comprehensive discussion.

Fixed-Time Distributed Event-Triggered Cooperative Guidance Methods for Multiple Vehicles with Limited Communications to Achieve Simultaneous Arrival

Aiming at the salvo-attack problem of multiple missiles, a distributed cooperative guidance law based on the event-triggered mechanism is proposed, which enables missiles with large differences in spatial location and velocity to achieve simultaneous attacks with only a few dozen information exchanges. It effectively reduces the generation of control commands and communication frequency, thereby reducing channel load and improving communication efficiency and reliability. Compared to traditional periodic sampling communication, the number of communications has been reduced by over 90%. The guidance process is divided into two stages. The first stage is the cooperative guidance stage, where missiles achieve consensus of the time-to-go estimates through information exchange. In this stage, each missile is designed with an event-triggered function based on its own state error, and the missile only updates and transmits its information in the communication network when the error meets the set threshold, effectively reducing the occupancy rate of missile-borne resources during the cooperation process. The second stage is the independent guidance stage, where missiles can hit the target simultaneously while keeping the communication network silent. This is achieved by ensuring that the time-to-go estimates of missiles can represent the real time-to-go after achieving consensus. By the design of the two-stage guidance law and the replacement of the event-triggered function, the cooperative guidance system can be ensured to remain stable in scenarios where the leader missile is present and destroyed, and this excludes Zeno behavior. The stability of the cooperative guidance law is rigorously proved by algebraic graph theory, matrix theory, and the Lyapunov method. Finally, the numerical simulation results demonstrate the validity of the algorithm and the correctness of the stability analysis.

Research on extremely low frequency electromagnetic wave model and simulation in wellbore communication

Over recent years, as digitalization and intelligence in oil wellbore have increased, so have the stricter requirements for wireless communication technology in terms of distance, accuracy, and portability. As a result, it’s necessary to rely on more advanced and efficient wireless communication technologies to meet the industry’s needs. However, traditional communication technologies such as cables and optical fibers have inherent shortcomings in construction, data interpretation, and cost. ELF electromagnetic waves are an ideal solution for communication in complex wellbore conditions due to long-distance communication and strong penetration capabilities, making it a highly effective option. Based on the theory of network splitting, this paper establishes a polygonal multiple-delays uncertainty coupled complex network model of ELF electromagnetic waves propagating through the casing in layered media and designs a controller, including expressions for the intensity of the magnetic and electric fields in different directions, and the propagation and distribution characteristics in different media. We determined that the optimal transmitting frequency of ELF electromagnetic waves under general conditions is 12.7 Hz. Based on field experiments, we verified that ELF electromagnetic waves can enable wireless wellbore communication within 1500 m without relays. We also analyzed the impact of casing thread deformation on ELF electromagnetic wave propagation due to high-temperature and high-pressure environments. We used simulation experiments to solve the distribution relationship between the electric and magnetic fields of the solenoids through casing and strata, as well as the coupling coefficients between the transmitting and receiving solenoids, and explore how different transmitting frequencies affect the efficiency of signal propagation. Both theories and experiments have verified the correctness of the model, and have also demonstrated the reliability and continuity of using ELF electromagnetic waves to achieve wireless wellbore communication, which provides a theoretical basis and feasibility for subsequent engineering applications.

Evaluating panel discussions in ESP classes: an exploration of international medical students’ and ESP instructors’ perspectives through qualitative research

This study investigates the effectiveness of panel discussions, a specific interactive teaching technique where a group of students leads a pre-planned, topic-focused discussion with audience participation, in English for Specific Purposes (ESP) courses for international medical students. This approach aims to simulate professional conference discussions, preparing students for future academic and clinical environments where such skills are crucial. While traditional group presentations foster critical thinking and communication, a gap exists in understanding how medical students perceive the complexities of preparing for and participating in panel discussions within an ESP setting. This qualitative study investigates the perceived advantages and disadvantages of these discussions from the perspectives of both panelists (medical students) and the audience (peers). Additionally, the study explores potential improvements based on insights from ESP instructors. Utilizing a two-phase design involving reflection papers and focus group discussions, data were collected from 46 medical students and three ESP instructors. Thematic analysis revealed that panel discussions offer unique benefits compared to traditional presentations, including enhanced engagement and more dynamic skill development for both panelists and the audience. Panelists reported gains in personal and professional development, including honing critical thinking, communication, and presentation skills. The audience perceived these discussions as engaging learning experiences that fostered critical analysis and information synthesis. However, challenges such as academic workload and concerns about discussion quality were also identified. The study concludes that panel discussions, when implemented effectively, can be a valuable tool for enhancing critical thinking, communication skills, and subject matter knowledge in ESP courses for medical students. These skills are transferable and can benefit students in various academic and professional settings, including future participation in medical conferences. This research provides valuable insights for ESP instructors seeking to integrate panel discussions into their curriculum, ultimately improving student learning outcomes and preparing them for future success in professional communication.

A visible light positioning system for coal mine personnel based on convolutional recurrent neural network

Visible Light Positioning (VLP) technology exhibits promising potential for underground coal mine positioning. While numerous studies have explored VLP in indoor environments, attention to VLP systems for underground mines still needs to be improved. In this paper, based on the traditional indoor visible light communication channel model, the effects of unique features on VLP, such as irregular walls, inclined and rotating receiving ends, and coal dust particles in underground mines, are considered and modeled in detail. In order to improve the accuracy and reliability of personnel VLP in complex mine environments, this paper proposes a deep-learning-based VLP system for underground personnel in coal mines, which consists of two LEDs and four photodetectors (PDs), where the four PDs are mounted on miners' helmets, in conjunction with the actual mine environment. Due to environmental factors and noise, there are apparent spatio-temporal characteristics in the received signal strength of the PDs. Therefore, the system adopts a convolutional recurrent neural network (CRNN) for feature extraction. In the experimental phase, the method's average localization error was 11.24 cm, with 90% of the localization errors within 20.4 cm. The experimental results show that the system has high positioning accuracy and meets the requirements of personnel positioning in underground mines.

Data-Driven Channel Modeling for End-to-End Visible Light DCO-OFDM Communication System Based on Experimental Data

End-to-end systems have been introduced to address the issue of independent signal processing module design in traditional communication systems, which prevents achieving global system optimization. However, research on indoor end-to-end Visible Light Communication (VLC) systems remains limited, especially regarding the channel modeling of high-speed, high-capacity Direct Current-biased Optical Orthogonal Frequency Division Multiplexing (DCO-OFDM) systems. This paper proposes three channel modeling methods for end-to-end DCO-OFDM VLC systems. The accuracy of the proposed methods is demonstrated through R-Square model fitting performance and data distribution analysis. The effectiveness of the proposed channel modeling methods is further validated by comparing the bit error rate (BER) performance of traditional receivers and existing deep learning (DL)-based receivers. The results show that the proposed methods can effectively mitigate both linear and nonlinear distortions. By employing these channel modeling methods, communication systems can reduce the spectral occupancy of pilot signals, thereby significantly lowering the complexity of traditional channel estimation methods. Thus, these methods are suitable for use in end-to-end VLC communication systems.

Digital Inertia: A Qualitative Study with a Caregiver Association Network About Informal Caregivers' Non-Use of IT Applications.

Informal caregivers, crucial contributors to healthcare, face myriad challenges in supporting individuals with health needs. While IT applications offer promising solutions, some caregivers hesitate to adopt them, favoring traditional communication approaches with healthcare and support providers. This study, conducted in Sweden, presents why caregivers are reluctant to use IT applications. Through a qualitative approach involving group interviews with caregiver association members, four key themes emerged, namely, need for in-person support with grief and stress, need for private support spaces, cognitive impairment, and financial constraints. Understanding these barriers is crucial for developing inclusive caregiving strategies that balance IT-based solutions with in-person assistance, promoting a sustainable caregiving support ecosystem.

A Facile Synthesis of TiO2-α-Ga2O3-Based Self-Powered Broad-Band UVC/UVA Photodetector and Optical Communication Study.

Traditional optical communication systems rely on single narrow-band PDs, which can expose confidential information and data to potential eavesdropping in free space. With advancements in technology, even optical communication in the UV spectrum, invisible to the sun, faces risks of interception. Consequently, broad-band PDs that combine optical encryption with algorithmic encryption hold significant promise for secure and reliable communication. This study presents a photodetector based on TiO2-α-Ga2O3 heterostructures, prepared via direct oxidation and hydrothermal reaction, demonstrating self-powered UVC/UVA broad-band detection capabilities. The PD exhibits response peaks at approximately 250 and 320 nm, with R of 42.16 and 59.88 mA/W and D* of 8.21 × 1013 and 9.56 × 1013 Jones, respectively. Leveraging the superior optical response characteristics of UVC and UVA wavelengths, this device has been employed to develop a communication system designed for data transmission. The proposed system features two independent channels: one for data transmission using UVC and another for key distribution using UVA. Secure communication is ensured through specialized encryption algorithms. In summary, this work offers a straightforward, cost-effective, and practical method for fabricating self-powered UVC/UVA broad-band PDs. This PD provides new insights into the development of multi-purpose, multi-band secure optical communication devices and holds promise for integration into multifunctional optoelectronic systems in the future.

Trafficking | Transmission | Translation: Exploring Embodiment as a Mode of Knowledge Construction in Science Art Installations

Abstract Science art practices are often framed as science communication in a manner that overlooks the capacity of the arts to provide engagement opportunities beyond discourse. The authors perform a thematic analysis of audience interviews from scientific media art installations that depict complex, intangible, invisible, and ephemeral scientific phenomena, specifically focusing on medical nanotechnology. The analysis reveals that visitors recognize sensorial experiences beyond traditional science communication, while scientists’ experiences expanded their definition of engagement. The authors argue that scientific media art practices act as sites of meaning-making and non-discursive engagement that create reflective and embodied contexts for encounters with emerging technologies.

The Communicology of a Blank Paper, a Void That Expresses

In this paper I attempt to trace the semiotic path of meaning experience from “nothing” into “something”. Traditional communication studies are problematic in 1. focusing on the message to the effect of ignoring the communicators; 2. choosing to overlook how yet-to-be signs acquire meanings in the communicative moments; and 3. tending to assume a “natural science” attitude toward the studied phenomenon so that embodied consciousness is either sidetracked or psychologized. Taking communicology as both the theory and methodology, I first describe the semiotic network in which blank paper, a nonconventional sign, acquires its signness in a specified communicative event. Then, I look inward to the relation of consciousness and embodiment. Finally, I argue that communication is such a life-world moment wherein non-expression is collectively constituted as a form of expression.

Adaptive Frame Structure Design for Sensing-Assisted Downlink Communication in the Vehicle-to-Infrastructure Scenario.

Vehicle-to-everything (V2X) is considered a key factor in driving the future development of intelligent transport, which requires high-quality communication and fast sensing of vehicle information in high-speed mobile scenarios. However, high-speed mobility makes the wireless channel change rapidly, which requires frequent channel estimation and channel feedback between a vehicle and the roadside unit (RSU), resulting in an increase in communication overhead. At the same time, the high maneuverability of vehicles leads to frequent switching and misalignment of communication beams, so the RSU must have better beam prediction and tracking capabilities. To address this problem, this paper proposes an adaptive frame structure design scheme for sensing-assisted downlink (DL) communication. The basic idea of the scheme involves analyzing the communication model during the vehicle's movement. This analysis aims to establish a theoretical relationship between the Symbol Error Rate (SER) and the following two key factors: the vehicle's starting position and the distance it travels across. Subsequently, the scheme leverages the vehicle's position data, as detected by the RSU, to calculate the real-time SER for DL communication. The SER threshold is set based on the requirements of DL communication. If the real-time SER is below this threshold, channel estimation becomes unnecessary. This decreases the frequency of channel estimation and frees up time and frequency resources that would otherwise be occupied by channel estimation processes within the frame structure. The design of an adaptive frame structure, as detailed in the above scheme, is presented. Furthermore, the performance of the proposed method is analyzed and compared with that of the traditional communication protocol frame structure and the beam prediction-based frame structure. The simulation results indicate that the communication throughput of the proposed method can be improved by up to 6% compared with the traditional communication protocol frame structure while maintaining SER performance.

Identification of multimodal vortex optical orbital angular momentum in multimode fiber speckle patterns

Orbital angular momentum (OAM) multiplexing technology is a highly promising approach that can significantly increase the data capacity of optical communication systems. However, traditional optical communication systems are prone to atmospheric disturbances such as turbulence, which can degrade transmission quality. To mitigate this issue, multimode fibers (MMFs) have been introduced to reduce the impact of turbulence on signals. Moreover, previous studies have primarily focused on the identification of single vortex beams, facing challenges in accurately recognizing multiplexed modes. To address this challenge, this chapter proposes a multi-label image classification optimization algorithm based on transfer learning. By utilizing the pre-trained MobileNet V2 model as a feature extractor, this network structure can accurately identify 8-bit, 16-bit, and 24-bit multiplexed OAM from speckle patterns in multimode fibers, even with small sample datasets, achieving classification accuracies exceeding 95%. This method overcomes the limitations of traditional optical communication systems that are susceptible to atmospheric disturbances, providing new possibilities for long-distance transmission and increased data capacity in optical communication systems.

The Impact of Digital Marketing on Consumer Behaviour

Abstract The use of communication techniques in marketing has become a fundamental component of effective marketing policy, representing an element of differentiation from the competition, which leads to obtaining, on the one hand, a competitive advantage, and on the other hand, to the consolidation of a long-term relationship with the consumer, ultimately determining their loyalty, with a notable effect on the financial outcomes of the organization. The selection of appropriate communication tools and channels, tailored to the interests of the targeted consumer segment requires a considerable effort on the part of marketers in the direction of deciphering consumer behaviour, understanding the influencing factors that shape it in the current economic and social climate, in which the use of digital technologies represents the most suitable means of initiating and conveying messages to consumers, as well as from consumers to the organization. The present study aims to emphasize the importance of using digital communication tools on the orientation of the purchase decision towards the products/services of an organization, without excluding, however, the need for an adequate use of traditional marketing communication tools. In the present article, the impact on consumer behaviour is analysed based on research from secondary data sources.

A Circular Shape Arc Slot Ultra-Wideband Antenna for Biomedical Applications

In modern communication systems, ultra-wideband (UWB) technology has garnered substantial attention due to its superior attributes compared to traditional narrowband communication systems. Over the past decade, UWB technology has also found applications in microwave-based imaging systems. This study introduces a simple planar coplanar waveguide-fed circular shape arc slot antenna designed specifically for biomedicine and microwave medical imaging applications. The proposed design is implemented on a 1.6-mm-thick FR4 substrate with a relative permittivity of 4.4 and a loss tangent of 0.0009. The antenna has physical dimensions of 26 mm × 29 mm and achieves an impressive bandwidth of 16.6 GHz, spanning 2.4 to 19 GHz. It exhibits a peak gain of 2.5 dBi and consistent omnidirectional radiation characteristics. Thorough temporal analysis validates the antenna's performance within acceptable limits, which is further affirmed through practical fabrication and testing, demonstrating strong agreement with simulation results.

Improving Disaster Response in Indonesia Through Culturally Integrated Communication Strategy

This study aims to analyze the communication strategies employed by the Regional Disaster Management Agency (BPBD) in disaster risk reduction efforts in Sidoarjo. Effective communication is crucial in ensuring community preparedness and resilience against disasters. This research adopts a qualitative method with a case study approach, using in-depth interviews, documentation, and literature review as data collection techniques. The primary data were analyzed using thematic analysis to identify critical patterns and insights. The results reveal that BPBD employs various communication strategies, including social media, public campaigns, and collaboration with local leaders. These efforts are designed to increase public awareness, disseminate early warning information, and foster community participation in disaster preparedness programs. Challenges identified include limited access to remote areas, inadequate resources, and low public engagement due to cultural and socio-economic factors. The discussion emphasizes the importance of integrating local wisdom and community-based approaches to enhance the effectiveness of disaster communication. The study concludes that combining modern technology and traditional communication methods is essential for comprehensive disaster risk reduction. Strengthening stakeholder collaboration and investing in capacity-building initiatives are also recommended for future improvements.

A comprehensive systematic review of privacy and security issues in Satellite Networks

The recent advancements in satellite networks have garnered significant interest due to their extensive geographic coverage and flexible deployment capabilities, offering a promising solution for global communications and transforming traditional communication methods. Despite these advancements, current satellite systems face challenges such as high propagation delays and inadequate coverage of high-latitude regions, particularly in Geostationary (GEO) systems. Low Earth Orbit (LEO) systems, which can address these issues, are primarily used for voice services, as seen in the Iridium system, but have encountered financial difficulties. This study aims to address the security issues in satellite networks, a critical concern as these networks increasingly rely on IP protocols and hybrid configurations of terrestrial nodes and satellite links. Previous works have identified various potential security attacks on satellite networks and proposed different solutions, but these solutions often lack comprehensive effectiveness and robustness. Our methodology involves analyzing the security vulnerabilities in satellite networks similar to the Iridium system, which includes inter-satellite links (ISL) and routers on each satellite. We review and evaluate existing security measures and propose enhancements to improve their effectiveness. Our results indicate significant vulnerabilities in current systems, but also show that with targeted improvements, security can be substantially enhanced. The implications of this study are profound, suggesting that more secure satellite networks can better support critical global communications and services, including broadband Internet and data services, thereby enhancing their reliability and user trust

Exploiting Cascaded Channel Signature for PHY-Layer Authentication in RIS-Enabled UAV Communication Systems

Reconfigurable Intelligent Surface (RIS)-assisted Unmanned Aerial Vehicle (UAV) communications face a critical security threat from impersonation attacks, where adversaries impersonate legitimate entities to infiltrate networks to obtain private data or unauthorized access. To combat such security threats, this paper proposes a novel physical layer (PHY-layer) authentication scheme for validating UAV identity in RIS-enabled UAV wireless networks. Considering that most existing works focus on traditional communication systems such as IoT and millimeter wave multiple-input multiple-output (MIMO) systems, there is currently no mature PHY-layer authentication scheme to serve RIS-UAV communication systems. To this end, our scheme leverages the unique characteristics of cascaded channels related to RIS to verify the legitimacy of UAV transmitting signals to the base station (BS). To be more precise, we first use the least squares estimate method and coordinate a descent-based algorithm to extract the cascaded channel feature. Next, we explore a quantizer to quantize the fluctuations of the channel gain that are related to the extracted channel feature. The 1-bit quantizer’s output findings are exploited to generate the authentication decision criteria, which are then tested using a binary hypothesis. The statistical signal processing technique is utilized to obtain the analytical formulations for detection and false alarm probabilities. We also conduct a computational complexity analysis of the proposed scheme. Finally, the numerical results validate the effectiveness of the proposed performance metric models and show that our detection performance can reach over 90% accuracy at a low signal-to-noise ratio (e.g., −8 dB), with a 10% improvement in detection accuracy compared with existing schemes.

Facial Expression Analysis Using Multi-label Classification

Emotions form the reflection of an individual's mental state. Automatic expression analysis and its recognition based on their facial landmarks are of critical use, particularly to understand the emotional states of physically disabled individuals like autistic children, deaf, dumb, and bedridden individuals. This approach helps in interpreting human emotions, which is crucial for designing computational models and interfaces that cater to their needs. While traditional research has focused on six basic emotion categories (happiness, surprise, sadness, anger, fear, disgust), your work expands this by exploring compound emotion categories. Compound emotions combine these basic categories to create nuanced emotional states. The research utilizes the CFEE_Database_230 dataset of facial expressions captured for analysis and training purposes. The proposed methodology has the following three steps: Analyze the dataset and extract the region of interest (ROI), Extract various statistical and potentially discriminating features and apply a multi-label classification approach to categorize sets of emotions. This involves comparing the feature values across different emotion classes and assigning appropriate labels, particularly focusing on compound emotion categories. Also, the research employs different classifiers and metrics to evaluate the effectiveness of the model. After applying the classification methods, the results are analyzed using various metrics to assess the accuracy and effectiveness of emotion recognition based on facial landmarks. Based on the findings, the Binary Relevance Method yielded the best performance with Mean Average Precision and hamming Loss of 0.7227±0.0344 and 0.1906±0.0227, respectively. Overall, the work contributes to advancing automatic emotion recognition by considering a broader range of emotional categories beyond the traditional basics. This is particularly beneficial for populations such as the physically disabled and autistic children, where traditional communication methods might be limited or challenging.

Needed competence for registered nurses working at a patient-centred telehealth service aimed to engage and empower people living with COPD: A five-month participatory observational study

BackgroundThe global population of older aged 65 and over is increasing, which means an increase in people living with long-term health conditions and multimorbidity. Implementing new digital health technologies enables increased patient empowerment and responsibility, and the ability to respond to changes in their condition themselves, with less involvement of healthcare professionals. Important parameters need to be addressed for this digitally enabled empowerment to be successful, these include increased individual and organizational health literacy, the establishment of joint decision-making activities among patients and healthcare professionals, and efforts that target the individual's ability to manage their condition, which include education to increase skills and providing technology for self-monitoring. ObjectiveTo identify needed competencies of digital healthcare professionals to be able to provide the needed services to service users with chronic obstructive pulmonary disease in a 24/7 digital healthcare service. MethodFive registered nurses' work was observed weekly for five months. In total 13 participatory observations were conducted. Data from the observations was transcribed and analysed through inductive content analysis. ResultsFive main categories were identified in the analysis; 1) tasks, 2) communication, 3) the relationships between the registered nurses, 4) service users, and 5) technology. These categories contain different competencies needed for registered nurses working in a digitalized healthcare system. ConclusionsFuture digital healthcare professionals will require several competencies, to be able to deliver proper care in a digital health community that goes beyond traditional healthcare competencies, including social, technological, and communication skills.

Actively Viewing the Audio-Visual Media: An Eye-Controlled Application for Experience and Learning in Traditional Chinese Painting Exhibitions

Traditional unidirectional communication through audio-visual media, such as video and slide, is a universal method of vividly narrating artifacts in museums. This traditional method is evolving with the integration of new technologies to engage visitors, enhancing their experience and learning. In recent years, eye-controlled interaction has been used to enrich traditional exhibitions, especially of ancient paintings. This article presents an eye-controlled application for actively viewing the audio-visual media of a traditional Chinese painting. Users can trigger animations and audio narrations by focusing their gaze on specific areas of the screen. To evaluate the value of experience and learning in integrating audio-visual media with eye-controlled interaction, we compared Eye-Controlled Application with the two baseline conditions (Video and Slide) through a comparison experiment (N = 40) in terms of user experience, learning outcome, cognitive load, intrinsic motivation, and visual behavior. The findings indicated the positive effects of Eye-Controlled Application on experience and learning, especially understanding. Users had stronger intrinsic motivation using Eye-Controlled Application, which contributed to positive learning outcomes. We found that Eye-Controlled Application changed visual behavior by increasing the proportion of gaze patterns and decreasing the proportion of movement patterns and scan patterns. The alteration in visual behavior primarily stemmed from the eye-controlled interaction, which directed the user’s focus toward specific areas, thereby guiding their attention to the necessary content. Additionally, the qualitative results suggested that each of the three conditions had its advantages and disadvantages. Importantly, the condition with Eye-Controlled Application carried potential risks of distraction, reduced efficiency, and increased burden. This study contributes to the potential of eye-controlled interaction for enhancing visitors’ experience and learning, providing new insights into the development of interactive audio-visual media within museums.