Advances In Communication Technologies Research Articles

Understanding the human element in scams: a multidisciplinary approach

ABSTRACT Scams are a widespread and persistent issue that have existed for thousands of years, evolving into a significant problem in modern society with the advancement of new media and communication technologies. This editorial attempts to provide a comprehensive understanding of the social and psychological mechanisms in scams through a multidisciplinary lens, drawing insights from communication studies, information systems, psychology, sociology, and economics. We aim to not only provide a robust framework for future scientific research, but also to map potential directions for developing effective scam prevention and intervention strategies in the future.

Non-tariff Measures in Services Sector: a PPML Analysis

ABSTRACT The paper presents an analysis of the tariff equivalent (AVEs) of regulations in the services sector, employing sectoral-level estimates derived from the gravity equation. Our findings indicate that advancements in information and communication technology have diminished the significance of traditional factors such as geographical distance and historical ties. Furthermore, we observe a positive correlation between trade barriers in the services sector and a nation’s level of economic development, suggesting that adherence to regulations tends to increase with per capita income. Moreover, our analysis reveals heterogeneity in protectionism across different sectors, with an apparent indirect relationship with the developmental stage of a country. On average, the gas sector emerges as the most heavily protected sector, whereas the air transport sector is relatively more open. AVE values across all sectors, Luxembourg, Singapore, Belgium, and Ireland emerge as the most open economies, while Bangladesh, Zimbabwe, Pakistan, and Tajikistan are the most restrictive.

A Systematic Review of Critical Thinking Development in Information and Communication Technology-Supported English as a Foreign Language Teaching from 2015 to 2024

Critical thinking is an essential skill for students in the 21st century and plays a pivotal role in language education. With the rapid advancement of Information and Communication Technology (ICT), English as a Foreign Language (EFL) education has significantly benefited from tools that support the development of critical thinking. While existing research has examined the impact of ICT on critical thinking in EFL classrooms, there is a lack of systematic reviews focusing specifically on the role of ICT tools in enhancing critical thinking within EFL teaching. This systematic review aims to address that gap by examining recent advancements and the effectiveness of ICT tools used in EFL instruction to foster critical thinking from 2015 to 2024, with a focus on tools such as digital mapping, WebQuest, and online games. The findings indicate that communicative, informative, and constructive ICT tools are widely used in EFL classrooms and are particularly effective in enhancing analysis, evaluation, and inference skills. This study provides an in-depth analysis of how these technologies are currently applied in EFL education to foster critical thinking skills. Additionally, the study also provides guidance for future research, highlighting the need to expand the use of emerging technologies, such as artificial intelligence (AI), virtual reality (VR), and augmented reality (AR), and explore their integration into diverse EFL contexts to maximize their potential in promoting critical thinking.

Meneroka Pengajian Al-Quran dan Tafsir di Media Sosial Menerusi Analisis Saluran YouTube

Abstract The digitalization era has witnessed various advancements in information and communication technology. In Malaysia, in particular, society has increasingly relied on new media channels to obtain quick and efficient information, such as social media. This involves issues related to religion, the economy, politics, and more. This article aims to examine YouTube channels that actively upload videos related to the Quran and exegesis for sharing with the audience. Additionally, it identifies the types of applications used in these videos. This study employs a qualitative method with a content analysis approach to gather data. The results reveal that out of 80 top-ranked Islamic channels on YouTube, 40 discuss the Quran and its branches of knowledge. Furthermore, there are a variety of video formats, including webinars, lectures, forums, debates, tutorials on Tajweed, Tarannum, and Qiraat, animations created with PowerPoint, Moovly, Powtoon, kinetic typography, GoAnimate, films, daily vlogs, games, and more. Therefore, through these discussions, it is hoped that Muslims can benefit from the information and knowledge obtained from YouTube sources while ensuring their authenticity and adherence to true Islamic teachings.

A Latency Composition Analysis for Telerobotic Performance Insights Across Various Network Scenarios

Telerobotics involves the operation of robots from a distance, often using advanced communication technologies combining wireless and wired technologies and a variety of protocols. This application domain is crucial because it allows humans to interact with and control robotic systems safely and from a distance, often performing activities in hazardous or inaccessible environments. Thus, by enabling remote operations, telerobotics not only enhances safety but also expands the possibilities for medical and industrial applications. In some use cases, telerobotics bridges the gap between human skill and robotic precision, making the completion of complex tasks requiring high accuracy possible without being physically present. With the growing availability of high-speed networks around the world, especially with the advent of 5G cellular technologies, applications of telerobotics can now span a gamut of scenarios ranging from remote control in the same room to robotic control across the globe. However, there are a variety of factors that can impact the control precision of the robotic platform and user experience of the teleoperator. One such critical factor is latency, especially across large geographical areas or complex network topologies. Consequently, military telerobotics and remote operations, for example, rely on dedicated communications infrastructure for such tasks. However, this creates a barrier to entry for many other applications and domains, as the cost of dedicated infrastructure would be prohibitive. In this paper, we examine the network latency of robotic control over shared network resources in a variety of network settings, such as a local network, access-controlled networks through Wi-Fi and cellular, and a remote transatlantic connection between Finland and the United States. The aim of this study is to quantify and evaluate the constituent latency components that comprise the control feedback loop of this telerobotics experience—of a camera feed for an operator to observe the telerobotic platform’s environment in one direction and the control communications from the operator to the robot in the reverse direction. The results show stable average round-trip latency of 6.6 ms for local network connection, 58.4 ms when connecting over Wi-Fi, 115.4 ms when connecting through cellular, and 240.7 ms when connecting from Finland to the United States over a VPN access-controlled network. 255,235,61. These findings provide a better understanding of the capabilities and performance limitations of conducting telerobotics activities over commodity networks, and lay the foundation of our future work to use these insights for optimizing the overall user experience and the responsiveness of this control loop.

Lightweight and High-Performance Microwave Absorbing Carbon Derived from Wasted bamboo

With the rapid advancements in communication, broadcasting, and statellite navigation technologies, the issue of electromagnetic wave pollution has emerged as a pressing research focus. Electromagnetic wave (EMW) absorbing materials provide a promising and practical solution to address this challenge. This paper presents a novel approach for fabricating electromagnetic wave absorbing material using in situ impregnation and pyrolysis of bamboo's inherent porous structure. By optimizing dielectric loss and integrating multiple magnetic iron phases, the material's impedance matching and magnetic loss characteristics were significantly enhanced, resulting in efficient electromagnetic wave absorption. Through adjusting the concentration of the precursor iron solution, the material attained a maximum reflection loss of -61.2dB and an bandwidth of 4.982GHz. Simulation results further validate the superior electromagnetic wave absorption performance of the modified material. In conclusion, this study introduces an eco-friendly electromagnetic wave absorbing composite, presenting a new pathway for the development of next-generation electromagnetic wave absorbing materials.

Using of Deep Learning in Beamforming Antenna Array

Digital beamforming (DBF) is a crucial technology for large antenna arrays, offering precise control over beam steering. This research introduces a novel method to enhance millimeter wave transmission by incorporating DBF with long-term memory (LSTM) based deep learning Our system utilizes digital signal processing and LSTM networks to optimize beamforming parameters instead of relying on traditional analog beamforming. The objective is to achieve high spectral efficiency. The methodology is executed in the programming language MATLAB and the obtained simulation outcomes validate a substantial enhancement in the metrics that evaluate performance, thereby demonstrating the potential of combining digital beamforming (DBF) with Long Short-Term Memory (LSTM) for forthcoming communication systems. Furthermore, the inclusion of LSTM in the process of digital beamforming presents a comprehensive comprehension of the proposed approach, which imparts valuable insights for advanced communication technologies. To substantiate the efficacy of the technique, several illustrative examples are employed to steer the beam pattern in the desired direction.

A Comprehensive Bibliometric Analysis of Distance Learning Assessments: Key Themes and Future Directions

Distance learning has become increasingly relevant, mainly fuelled by advances in information and communication technology (ICT) and emergency situations such as the COVID-19 pandemic. Innovations in assessment and evaluation methods are key to improving the quality of education in the context of distance learning. This study aims to identify, analyse and map the main themes and provide recommendations for new directions for future research related to distance learning assessment. This research is quantitative-descriptive in nature using bibliometric analysis techniques. Bibliographic data was taken from a credible scientific database on the Scopus database in the range of 2020-2024 using the keyword ‘Assessment for distance learning’. The data obtained was analysed and the relationship between keywords was mapped. Based on the results of the analysis it can be concluded that the 10 major themes and research trends related to distance learning assessment include distance learning (131), higher education (43), e-learning (40), distance education (34), Covid-19 (30), assessment (24), pandemic (23), blended learning (17), online assessment (16), online education (15). The results of this study can provide a framework for understanding distance learning assessment in a broader and cross-disciplinary context

Modular Web-based Learning Model to Address Underdeveloped ICT Infrastructure for Smart E-learning Education System

Advancements in Information and Communication Technology (ICT) enhance learning and instructional practices, generating chances for novel techniques and tools while simultaneously transforming the learning model. Historically, smart education models mostly consisted of qualitative investigations that delineated the conceptual structure and its implications for the Smart E-learning Education System (SEES). While these theoretically organized SEES can enhance student learning, facilitate peer and instructor communication, and improve teaching practices—thereby aiding in the comprehension of the status of learners and needs and offering real-time synchronous/asynchronous guidance—many qualitative investigations conducted in the past lack empirical evidence to substantiate the prioritization of E-Learning scheduling. This research first examined the technological barriers to implementing the SEES in developing nations. As a result, the suggested framework for the SEES based on underdeveloped ICT has been introduced. The system utilizes an integrated online/offline Web-Based Learning Model (WLM) incorporating a Service-oriented Architecture (SA) architecture to create SEES. The online mode is enabled for a WLM when an internet connection is accessible. The offline variant of the system is provided in a packed format and is used when Internet access is unavailable in an isolated classroom. A working example was launched to get input from learners and instructors across diverse educational levels. The trial installation and survey results confirm the viability and benefits of the suggested system.

Experimental investigation to analyze the electromagnetic radiation exposure from wireless communication devices

Recent advancements in wireless communication technologies have led to the existence of a higher amount of electromagnetic radiation (EMR) in the atmosphere. The intensity of these exposed radiation depends upon the frequency of operation from these communication devices. The paper presents a scientific study on assessing the intensity of electromagnetic waves emitted by different wireless communication devices with human beings based on analyzing the electric field, magnetic field and power density generated from various electronic gadgets and wireless communication devices like smartwatch, laptop, mobile phone, nano-station, headset and mobile towers using an electro-smog meter (Electromagnetic Field (EMF) Meter - PCE-EM 29). The interaction is being studied by placing different wireless communication equipment near to human body. Based on the study, it is identified that a portion of the EMR is absorbed by nearby human beings and is identified by differentiating the field characteristics with and without its presence and is tested in near or far away from the devices. From the test results, it is identified that a portion of the EMR is absorbed by the body parts of the human beings near to the wireless device. This result could act as scientific evidence providing the effects of EMR interactions like electromagnetic hypersensitivity symptoms on humans. Similarly, most of the field exposures from the radiating devices are highly influenced by all the biotic community including human beings based on its interaction. All these field exposures to radiation from various wireless communication devices are direct indications of the Specific Absorption Rate (SAR).

Quantitative Prediction of Polymer Dielectric Constants Using an Improved Mathematic Correlation Based on Molecular Polarity Components

ABSTRACTThe advancement of communication technology has significantly promoted the development of dielectric polymers. However, the quantitative prediction of dielectric constant for rapid material screening is hard due to the low precision of existing theories. In this paper, a new model was developed to calculate the dielectric constants of organic materials through theoretical deduction correlating to the dielectric and polar Hansen solubility parameter (HSP) functions (). This model treated the permanent dipole moments as the primary function determining the dielectric constant and the corresponding polar HSP, which was demonstrated to be in good agreement with experimental data and produced reasonable fitting for organic solvents, thermoplastic polymers, and thermoset polymers, yielding R2 of 0.7488, 0.8104, and 0.7450, respectively, and it demonstrated better fitting with R2 of 0.9043 when applied to organic solvents having low hydrogen bonding component (, < 12.5). This new correlation produces the highest accuracy of prediction when compared to the existing models and provides a better mathematical tool to help design and screen dielectric polymers.

Reliable and cost-efficient session provisioning in CRNs using spectrum sensing as a service

With the advancement of wireless communication technologies, and the growing number of wireless and IoT applications that demand various types and volumes of data, Sensing as a Service (SaaS) has emerged as a necessary enabling business model for many of those applications. Spectrum Sensing as a Service (SSaaS) has also emerged as a form of SaaS that is concerned with the monitoring of wireless spectrum to facilitate its safe reuse by cognitive radio-enabled wireless users. SSaaS was primarily motivated by the need for a low-cost, accurate, and reliable spectrum sensing service to support a plethora of heterogeneous wireless devices and applications. Under the SSaaS model, clients need to pay the service provider for the sensing service they receive. In this paper, we address the problem of allocating spectrum channels to links of a given communication session in a cognitive radio network (CRN) that utilizes SSaaS. The objective is to allocate channels such that the worst link availability among the session is maximized and the spectrum access cost is minimized. A number of multi-objective evolutionary optimization algorithms (MOEAs) were used to solve this multi-objective optimization problem. Extensive experimentation was conducted to compare between these algorithms and identify the best ones to use. We also propose a post-processing greedy algorithm to further enhance the solution obtained by a MOEA algorithm. Results show that an improvement of up to 20% can be achieved using the proposed greedy algorithm under some network settings.

Wi-Fi Sensing Techniques for Human Activity Recognition: Brief Survey, Potential Challenges, and Research Directions

Recent advancements in wireless communication technologies have made Wi-Fi signals indispensable in both personal and professional settings. The utilization of these signals for Human Activity Recognition (HAR) has emerged as a cutting-edge technology. By leveraging the fluctuations in Wi-Fi signals for HAR, this approach offers enhanced privacy compared to traditional visual surveillance methods. The essence of this technique lies in detecting subtle changes when Wi-Fi signals interact with the human body, which are then captured and interpreted by advanced algorithms. This paper initially provides an overview of the key methodologies in HAR and the evolution of non-contact sensing, introducing sensor-based recognition, computer vision, and Wi-Fi signal-based approaches, respectively. It then explores tools for Wi-Fi-based HAR signal collection and lists several high-quality datasets. Subsequently, the paper reviews various sensing tasks enabled by Wi-Fi signal recognition, highlighting the application of deep learning networks in Wi-Fi signal detection. The fourth section presents experimental results that assess the capabilities of different networks. The findings indicate significant variability in the generalization capacities of neural networks and notable differences in test accuracy for various motion analyses.

Enhancing Data Security through Digital Image Steganography: An Implementation of the Two Least Significant Bits (2LSB) Method

The rapid advancement of digital communication technologies has heightened the demand for robust data security methods, particularly for safeguarding sensitive information against cyber threats. Steganography, the art of concealing data within digital media, offers an effective means of securing communication by masking the very existence of hidden messages. This study evaluates the Two Least Significant Bits (2LSB) method as an enhancement to the conventional Least Significant Bit (LSB) technique, focusing on improving storage capacity and resistance to detection. The research employs a quantitative methodology, conducting experiments to analyze the impact of data embedding on image quality using metrics such as Mean Squared Error (MSE) and Peak Signal-to-Noise Ratio (PSNR). Data embedding was tested on images of varying sizes and resolutions, with results compared before and after embedding. The study also evaluates the system’s tolerance to compression and robustness against steganalysis attacks, such as histogram analysis and noise detection. The results demonstrate that the 2LSB method significantly enhances storage capacity while maintaining high image quality. For instance, PSNR values remained above 40 dB across all tested images, indicating minimal visual distortion. The method also showed resilience to lossless compression formats such as PNG, with minimal impact on data integrity. However, lossy compression formats like JPEG posed challenges in maintaining the embedded data. The MSE values before and after embedding were minor, ensuring that the hidden data remained undetectable under standard analysis. This research contributes to developing more efficient and secure steganography techniques, providing practical applications in protecting sensitive data during transmission. The findings underline the 2LSB method's potential as a viable solution for digital security, balancing enhanced storage capacity with robust resistance to detection. Future work should further explore integrating advanced encryption with 2LSB to strengthen data protection in diverse digital environments

In-situ Construction of Petal-liked porous Co coating layers for electromagnetic wave absorption materials with rich interface-polarization

With the rapid advancements in 5G and communication technology, electromagnetic wave (EMW) absorption materials play a crucial role in reducing interference, enhancing the efficiency and stability of communication equipment, and minimizing maintenance requirements. However, the challenge remains in effectively utilizing cost-effective raw materials with simple synthesis conditions to achieve highly consistent product quality and superior EWM absorption performance. This study employs carbon nanofibers (CNFs) derived from polyacrylonitrile (PAN) as substrates and utilizes electrodeposition technology to create a composite material that exhibits both magnetic and dielectric properties. The results show that the petal-like porous Co composite CNFs (Co/CNFs) demonstrates excellent impedance matching and significant EMW absorption capabilities, which can be attributed to synergistic microstructural effects and multiple loss mechanisms. At a filling ratio of 20 wt% and a thickness of 1.8 mm, the Co/CNFs achieves a minimum reflection loss of −45 dB, extending the effective absorption bandwidth to 4.6 GHz. Performance assessment through power loss density (PLD) and radar cross-section (RCS) simulations evaluates the material’s capabilities, confirming the enhanced performance of Co/CNFs compared to the perfect electrical conductor (PEC). This efficient preparation method holds substantial potential for practical applications and serves as a comprehensive guide for achieving a balance between high performance, efficiency, and cost-advantages.

Optical soliton noninteraction transmission in optical communication systems

The building of the national communication infrastructure and growing demand for data traffic both depend heavily on the advancement of optical soliton communication technology. In particular, by studying the interaction of optical solitons, some methods of controlling optical solitons can be explored to design more stable and efficient optical communication systems. In this paper, the interactions between optical solitons are studied based on the theory of generalized Schrödinger–Hirota equation. By studying the amplitude ratio, spacing and phase difference of the optical solitons, the interactions between the optical solitons occurring in the optical fiber transmission process are attenuated. The noninteraction transmission of optical solitons are realized with small spacing between them. The conclusions of this paper are not only of great significance for the in-depth understanding of the nature of optical soliton interactions, but also of great practical value for promoting the application of optical solitons in optical communications and other fields.

Exploring determinants of visitor’s e-WOM in the virtual art exhibition with an extended American Customer Satisfaction Index Model

Purpose By applying the American Customer Satisfaction Index (ACSI) model to virtual art exhibitions, this research aims to reveal insights into the factors impacting visitor satisfaction and electronic word-of-mouth (e-WOM). Furthermore, the investigation of exhibition promotion seeks to understand how external factors contribute to the overall visitor experience in virtual art exhibitions. Design/methodology/approach With advancements in virtual communication technology and the transformative impact of the COVID-19 pandemic in recent years, there has been a notable surge in the popularity of virtual art exhibitions based on the Internet. This study uses the ACSI model to examine visitor satisfaction and e-WOM in virtual art exhibitions. Additionally, it explores the influence of exhibition promotion on the ACSI model. Findings Key findings revealed that 1) both promotion efforts and e-WOM exhibited significant relationships with the ACSI model, and 2) most of the relationships within the ACSI model were consistent with previous research outcomes. Originality/value This study extends the ACSI model’s application to virtual art exhibitions, enhancing its relevance. Additionally, it addresses the knowledge gap concerning the direct impact of promotion on audience expectations and its relationship with the ACSI model in virtual art exhibitions. Furthermore, the research explores the influence of customer satisfaction on electronic word-of-mouth in exhibitions, offering valuable insights for exhibition evaluation systems. The study serves as a guide, providing data and models for researchers investigating virtual art exhibitions.

Research on the Influencing Factors of High-Quality Development of Service Industry Under Digital Network Computing

Faced with the growing demand for personalized services and the challenge of high service quality standards in the market, the traditional service industry model is no longer able to meet current needs, and transformation and upgrading are urgently needed. Therefore, it is particularly crucial to deeply analyze how digital network computing can effectively empower and accelerate the high-quality development process of the service industry, while identifying and analyzing the core influencing factors in this process. Digital network computing relies on vast digital knowledge and information resources, with highly interconnected network infrastructure as the cornerstone, integrating advanced information and communication technologies to achieve real-time transmission, processing, and analysis of data, thereby driving the continuous emergence of intelligent decision-making and innovative applications. Its distinctive characteristics include high network interconnectivity, deep data mining and utilization, intelligent decision support, and continuous technological innovation drive. The purpose of this study is to deepen the understanding of the internal mechanism of the integration and development of digital network computing and the service industry, and to reveal the multiple paths and key factors that promote high-quality development of the service industry. Through system analysis, we hope to provide scientific decision-making basis for policy makers, valuable strategic suggestions for service enterprises on the road of digital transformation, and jointly promote the service industry to move toward a more prosperous, efficient, and sustainable new stage of development.

Feeling Grounded: Exploring the Sense of Groundedness in Cultural Tourism Driven by Live Streaming Technology

As information and communication technology advances, the on-site experience of traditional field tourism is being transformed into a virtual experience under digital tourism. The sense of groundedness occurs when tourists connect to the geography, humanity, and history of destination. Little is known about how technology, marketing, and tourism resources can be combined to enrich the authenticity of the virtual tourism experience. This study explores the main characteristics of groundedness in cultural tourism to address this research gap. It develops and validates the scale for measuring tourism experience based on live streaming technology. The findings also reveal groundedness as a driver of tourists’ willingness and behavior to participate. The study theoretically promotes the development of groundedness and the emerging research on digital cultural tourism marketing. Meanwhile, the study results provide stakeholders with an attractive and implementable tourism perceptual experience—groundedness—implying references for overall sustainable destination development.

EXPRESS: Individual Sellers’ Social Media Participation and Sales Performance in Peer-to-Peer Marketplaces: Evidence from a Quasi-Natural Experiment

Recent advancements in communication and social technologies have resulted in the growth of peer-to-peer (P2P) marketplaces, such as Xianyu and Poshmark. Individual sellers in these markets, most of whom are unbranded and lack credibility, often face immense challenges in building trust to facilitate P2P transactions. We consider the potential of sellers’ use of social media to establish trust and drive sales. Specifically, we address whether social media use benefits the sales performance of individual sellers, and how social media use affects customer retention and acquisition. We draw on social capital theory to explore the theoretical mechanisms by which social media participation may affect sales, hypothesizing that such participation enables the seller to accumulate social capital and develop trust. We empirically test this by exploiting a quasi-natural experiment wherein a large P2P marketplace for second-hand goods (Xianyu) unexpectedly removed its social media feature (Fishponds). We employ a difference-in-differences design, leveraging a proprietary dataset capturing social media participation and sales activities for individual sellers, covering more than 180,000 transactions over a multi-week period around the event. We find that sellers who initially participated in social media channels experienced a significant decline in sales after the shutdown, which is attributable to poorer customer retention and acquisition. We explore heterogeneity in the effects and find that the sellers who benefit most from social media participation are those with the most to gain from trust-building. An additional online controlled experiment provides further evidence of the trust-building mechanism. Our study implies individual sellers can harness social media to generate additional sales from existing and new customers. These insights are important, as they speak to the value of social media channels as drivers of trust in P2P marketplaces.