Content Characteristics Research Articles

Characteristic features of toxic metal content in hair samples of foreign students at RUDN University from different geographic regions

BackgroundThis study explores the regional variations in toxic metal accumulation among RUDN University students from various global regions. MethodsThis comparative analysis examined hair samples from students hailing from different regions, including Russia, Asia, the Middle East, Africa, and Latin America. The concentrations of Aluminium (Al), Arsenic (As), Cadmium (Cd), Mercury (Hg), Lead (Pb), and Tin (Sn) were measured in the hair samples. The data was then evaluated using regression models to assess the link between the region of residence and toxic metal content in the hair. ResultsThe analysis indicated significant regional variations in the levels of toxic metals in the students' hair. The highest content of Al, Cd, and Pb was observed in students from Africa (13.542, 0.028, 0.794 µg/g) and Latin America (9.947, 0.025, 0.435 µg/g). Arsenic levels in students from all regions exceeded that of Russian students by over two-fold. No substantial group differences were found in the Sn content. The regression models suggested that residing in Asia, Africa, and Latin America was a predictor of high Hg levels in hair (0.130, 0.096, 0.227 µg/g). Living in Africa was significantly associated with higher Pb levels (0.794 µg/g), and living in Latin America was close to significantly associated with the Cd level in the hair (0.025 µg/g). ConclusionThis study confirmed an increased accumulation of toxic metals, especially Hg, Cd, and Pb, in students primarily from Latin America and Africa. The findings highlighted the importance of understanding the regional variations in toxic metal accumulation to address associated health risks and the potential impact on students' well-being and academic performance. These insights may guide the development of targeted interventions to reduce exposure to toxic metals in students from various regions around the world.

Linguistic Markers of Inherently False AI Communication and Intentionally False Human Communication: Evidence From Hotel Reviews

To the human eye, AI-generated outputs of large language models have increasingly become indistinguishable from human-generated outputs. Therefore, to determine the linguistic properties that separate AI-generated text from human-generated text, we used a state-of-the-art chatbot, ChatGPT, and compared how it wrote hotel reviews to human-generated counterparts across content (emotion), style (analytic writing, adjectives), and structural features (readability). Results suggested AI-generated text had a more analytic style and was more affective, more descriptive, and less readable than human-generated text. Classification accuracies of AI-generated versus human-generated texts were over 80%, far exceeding chance (∼50%). Here, we argue AI-generated text is inherently false when communicating about personal experiences that are typical of humans and differs from intentionally false human-generated text at the language level. Implications for AI-mediated communication and deception research are discussed.

Agony to Enlightenment: Parallels between Rafael Lechowski’s Quarcissus and T.S. Eliot’s Four Quartets

Eliot’s Four Quartets stands as one of the most influential poetic works of the 20th Century. Therefore, academics have approached it from many different angles, among which one may mention its musicality, the references it contains, its composition, and the belief systems that converge in it, such as Christianity, Hinduism, and Buddhism. Rap music, on the other hand, is generally assumed to be a cultural product that lacks profound insights on the subjects it touches upon precisely because it is built for entertainment, not academic analysis. However, although rap music is generally regarded as non-academic, Rafael Lechowski’s extensive rap work entitled Quarcissus: El arte de desamar has divided criticism because of the way in which it engages with the subject of emotional pain. This article argues that Lechowski’s work shares both structural and content features with Eliot’s Four Quartets; particulary regarding Buddhist principles, which is established by comparing the four sections that make up both texts.

Drivers of News Sharing: How Context, Content, and User Features Shape Sharing Decisions on Facebook

What makes people share political news on Facebook? Prior studies have identified how different features predict audiences’ likelihood to share news on social media – the so-called shareworthiness of news. However, we still know very little about the relative contributions of these different features for predicting why people decide to share news. We extend the literature by using an experimental design that can compare the relative importance of several key features that contribute to shaping citizens’ sharing decisions: a conjoint experimental design. We use an identical layout to Facebook and a probability sample of Norwegian citizens. We find that particularly content characteristics are important, and that popularity cues and message congruence is conditional on some user characteristics such as age.

Children's Musical as a Popular Genre of Ukrainian Stage Art in 1960s-1990s: Formation and Development

The purpose of the article is to identify the peculiarities of formation and the main trends in the development of children's musical as a popular genre of Ukrainian stage art in the 1960s-1990s. Research methodology. The historical and cultural method was used to summarise the factual material related to the time of creation and the logic of development of the children's musical in the Ukrainian stage art of the 1960s-1990s. The methods of art historical and genre-stylistic analysis were applied to help identify specific artistic and aesthetic, genre and stylistic features in the productions of children's musical on the stages of Ukrainian theatres. Scientific novelty. The history of the formation and development of the Ukrainian children's musical in the stage art of the 1960s-1990s is studied; its musical, artistic, staging and performance features are revealed. The chronological sequence of writing the most significant in the context of the development of the genre of the first national children's musicals is presented. The contribution of Ukrainian composers (Zh. Kolodub and L. Kolodub, O. Bilash, I. Poklad, S. Bedusenko) and directors (P. Kolisnyk, M. Lukavetskyi) in the formation of the national musical for children's audiences is revealed. Children's musicals by Ukrainian composers included in the "golden fund" of national stage art are analysed ("Fox Mykyta" (libretto by R. Kudlyk) and "Tom Sawyer" (libretto by M. Petrenko based on Mark Twain's novel) by B.-Yu. Yanivskyi). Conclusions. The process of integrating the musical genre into the Ukrainian stage art of the last third of the 20th century took place in accordance with the peculiarities of the socio-cultural space of that time, socio-political events and artistic trends. The creative rethinking of content and structural features of the Western genre invariant in the 1960s-1990s became the basis for the formation of the national Ukrainian children's musical as a factor in the internationalisation of the world music and stage culture. At the same time, the formation of the Ukrainian children's musical is connected with the process of nationalisation of the genre, as evidenced by the reliance of the libretto on stories from folklore and traditional Ukrainian culture, the introduction of traditional principles and techniques inherent in the stage art of Ukraine. The peculiarities of the formation and further development of children's musicals in Ukraine were conditioned by the creative searches of domestic composers (B.-Yu. Yanovskyi, I. Poklad, S. Bedusenko, Zh. and L. Kolodub, E. Lapeika, O. Kolomiitseva, A. Bondarenko) and theatre directors. The productions of children's musicals from the 1960s-1990s allow us to talk about the rethinking of the Western archetype of the genre and the beginning of the formation of a national Ukrainian musical.
 Key words: children's musical, Ukrainian stage art, children's musical theatre, genre, production and performance features.

EMERGING DESIGN TRENDS IN SOCIAL MEDIA AND ITS IMPACT ON BUSINESS EFFICIENCY AND GROWTH IN INDIA

Until the late 1990s, business was not accustomed to radio, newspapers, or television. However, the media revolution began in 2000 with the birth of social media. Like other forms of media, social networks are a means of communication. However, it provides more social interaction using highly available and scalable methods. Customers and businesses alike can benefit from social media. The effectiveness of social media marketing strategies heavily relies on the visual designs used in content creation, making it an essential element for businesses to consider.This research paper explores the impact of emerging design trends in social media on business efficiency and growth in India. Social media has become an integral part of the marketing strategy for businesses of all sizes in India. With the rise of new technologies, social media platforms are constantly evolving, and design trends are emerging to keep up with the changing needs and preferences of users. This research paper aims to analyze the impact of these emerging design trends on the efficiency and growth of businesses in India. The research methodology involves a systematic review of existing literature, followed by qualitative research using case studies and interviews with industry experts. The findings suggest that businesses that adopt emerging design trends in social media can achieve higher levels of engagement, increased brand awareness, and improved customer loyalty, leading to greater efficiency and growth. The paper concludes with recommendations for businesses in India to incorporate emerging design trends in their social media strategy to enhance their efficiency and growth in the competitive market.Some of the emerging design trends that have been identified and analyzed in this research paper include the use of video content, interactive features, user-generated content, and personalized marketing. These trends have been found to have a significant impact on user engagement and brand perception, thereby affecting business efficiency and growth.The research findings also indicate that while the adoption of emerging design trends can lead to benefits for businesses, it is essential to consider the target audience and their preferences when implementing these trends. For instance, younger audiences are more likely to engage with video content and interactive features, while older audiences may prefer more traditional forms of marketing. Therefore, businesses need to tailor their social media strategy based on their target audience to achieve maximum benefits.Overall, this research paper highlights the importance of incorporating emerging design trends in social media strategy for businesses in India. As social media continues to evolve, businesses need to stay up-to-date with the latest design trends to remain relevant and competitive in the market. By adopting these trends, businesses can enhance their efficiency and growth, leading to greater success in the long run.

Does knowledge make a difference? Understanding how the lay public and experts assess the credibility of information on novel foods.

Drawing on Metzger's dual-processing model of credibility assessment, this study examines how individuals with varying topical knowledge (laypersons vs experts) assess the credibility of information on novel foods. Online focus group discussions reveal that both groups share similar motivations for assessing the credibility of information on novel foods (e.g. personal relevance and concerns about the impact of unverified information on others). However, they differ in the barriers they encounter during the assessment of information credibility. Both groups employ analytical (e.g. evaluating content quality) and intuitive methods (e.g. looking at source credibility) to assess the credibility of novel food-related information. However, they differ in the cues used for credibility assessment. Laypersons tend to rely on superficial heuristics (e.g. social endorsement cues or surface features), whereas experts rely more on content features and scientific knowledge to evaluate information credibility. Theoretical and practical implications are discussed.

Ebublio: Edge-Assisted Multiuser 360° Video Streaming

As one of the most important manifestations of virtual reality (VR), 3600 panoramic videos in recent years have experienced booming development due to the desire for immersive and interactive experiences. Compared to traditional videos, 3600 videos are featured with uncertain user field of view (FoV), more sensitive delay tolerance, and much higher bandwidth requirement, bringing unprecedented challenges to 3600 video streaming. Meanwhile, the development of 5G and mobile edge computing starts to pave the way for high-bandwidth low-latency video streaming. Some preliminary works focus on either individual FoV prediction or multi-user QoE oriented cache strategy design, while how to design a holistic solution toward optimizing the overall user QoE with considerations over fairness and long-term system cost remains a non-trivial problem. In this paper, we propose Ebublio, a novel intelligent edge caching framework to address the aforementioned challenges in 3600 video streaming. Ebublio consists of a collaborative FoV prediction (CFP) module and a long-term tile caching optimization (LTO) module to jointly optimize the long-term user QoE and system cost. The former module integrates the features of video content, user trajectory, and other users records for combined prediction. The latter one employs the Lyapunov framework and a subgradient optimization approach towards the optimal caching replacement policy. Our trace-driven evaluation demonstrates the superiority of our framework, with about 42% improvement in FoV prediction, and 36% improvement in QoE at similar traffic consumption.

Research on Weibo New Word Recognition based on Weibo Data and Statistical Information

One of the key challenges in the field of Chinese information processing is the recognition of Weibo new words, which has a profound impact on machine translation and text classification. As Weibo has become the most used social platform for internet users, mining new vocabulary from Weibo data not only helps to deeply understand the data itself, but also provides personalized recommendation services for users. Although a large amount of research has focused on the recognition of Weibo new words, specialized research in this field is still scarce. In this article, we propose a Weibo new word recognition strategy that combines Weibo content features and statistical information. Firstly, extract repetitive vocabulary from Weibo topic names, and then use various methods such as absolute frequency, relative frequency, mutual information, and information entropy to filter for incorrect vocabulary. The experimental results show that by setting appropriate thresholds, incorrect vocabulary can be effectively filtered out, thereby improving recognition performance.

Unpaired Artistic Portrait Style Transfer via Asymmetric Double-Stream GAN.

With the development of image style transfer technologies, portrait style transfer has attracted growing attention in this research community. In this article, we present an asymmetric double-stream generative adversarial network (ADS-GAN) to solve the problems that caused by cartoonization and other style transfer techniques when they are applied to portrait photos, such as facial deformation, contours missing, and stiff lines. By observing the characteristics between source and target images, we propose an edge contour retention (ECR) regularized loss to constrain the local and global contours of generated portrait images to avoid the portrait deformation. In addition, a content-style feature fusion module is introduced for further learning of the target image style, which uses a style attention mechanism to integrate features and embeds style features into content features of portrait photos according to the attention weights. Finally, a guided filter is introduced in content encoder to smooth the textures and specific details of source image, thereby eliminating its negative impact on style transfer. We conducted overall unified optimization training on all components and got an ADS-GAN for unpaired artistic portrait style transfer. Qualitative comparisons and quantitative analyses demonstrate that the proposed method generates superior results than benchmark work in preserving the overall structure and contours of portrait; ablation and parameter study demonstrate the effectiveness of each component in our framework.

Pembuatan Mobile Learning untuk Ibu Mengenali dan Mengatasi Permasalahan Anak Usia Dini Sulit Makan Menggunakan Metode Waterfall

The research aims to develop a mobile learning app for mothers to help them identify and solve early childhood problems that are difficult to eat. The development method used is the Waterfall method, which involves structured stages such as needs analysis, planning, implementation, testing, and maintenance. At the need analysis stage, we conducted surveys and interviews with mothers who had early childhood to understand the challenges they faced in dealing with their children's eating problems. Next, at the design stage, we design an application interface, educational content, and interactive features that will help you understand this issue better. Application deployment involves software development based on the design that has been made. After that, we tested the application to ensure its functionality and effectiveness in helping mothers identify and deal with early childhood eating problems. We also involved moms as test users during this phase to get valuable feedback. The results of this study show that the use of the Waterfall method in the development of Mobile Learning for early childhood problems that are difficult to eat produces applications that can help mothers significantly. The application provides relevant information, practical advice, and community support for mothers facing this problem. In conclusion, the Waterfall method has proven to be effective in producing mobile learning applications that are useful to mothers in dealing with early childhood feeding problems. The app has the potential to enhance mother's understanding of their children's nutrition and provide better solutions to dealing with eating problems in early childhood.

Co-designing an online treatment decision aid for men with low-risk prostate cancer: Navigate.

To develop an online treatment decision aid (OTDA) to assist patients with low-risk prostate cancer (LRPC) and their partners in making treatment decisions. Navigate, an OTDA for LRPC, was rigorously co-designed by patients with a confirmed diagnosis or at risk of LRPC and their partners, clinicians, researchers and website designers/developers. A theoretical model guided the development process. A mixed methods approach was used incorporating (1) evidence for essential design elements for OTDAs; (2) evidence for treatment options for LRPC; (3) an iterative co-design process involving stakeholder workshops and prototype review; and (4) expert rating using the International Patient Decision Aid Standards (IPDAS). Three co-design workshops with potential users (n= 12) and research and web-design team members (n= 10) were conducted. Results from each workshop informed OTDA modifications to the OTDA for testing in the subsequent workshop. Clinician (n= 6) and consumer (n= 9) feedback on usability and content on the penultimate version was collected. The initial workshops identified key content and design features that were incorporated into the draft OTDA, re-workshopped and incorporated into the penultimate OTDA. Expert feedback on usability and content was also incorporated into the final OTDA. The final OTDA was deemed comprehensive, clear and appropriate and met all IPDAS criteria. Navigate is an interactive and acceptable OTDA for Australian men with LRPC designed by men for men using a co-design methodology. The effectiveness of Navigate in assisting patient decision-making is currently being assessed in a randomised controlled trial with patients with LRPC and their partners.

Standing out from the crowd: When and why color complexity in social media images increases user engagement

Firms increasingly rely on images to drive user engagement with their social media content. However, evidence is limited on when and why image characteristics can draw social media users’ attention and increase engagement. In this research, the authors theorize that color complexity in images can serve as an external cue that draws social media users’ attention and provokes a shift from the peripheral processing mode to the central processing mode. This shift can result in deeper processing of the social media post that features the image, thus increasing the likelihood of the users’ engagement with the post. They further reveal heterogeneity in the effect of color complexity due to the time of day when the users are exposed to the image, image height, and sentiment and complexity in the text accompanying the image. The results are consistent across an empirical analysis of two proprietary Facebook datasets from distinct industries and time periods and confirmed by two biometric eye-tracking experiments that provide process evidence. The findings have important implications for both content marketers and academics as they seek to identify content features that can maximize user engagement on social media.

Arbitrary style transfer based on Attention and Covariance-Matching

Arbitrary style transfer has broad application prospects and important research values, and it is a research hotspot in the field of computer vision. Many studies have shown that arbitrary style transfer achieves remarkable success. However, existing methods may produce artifacts and sometimes lead to distortion of the content structure. To overcome this limitation, this paper proposes a novel Attention-wise and Covariance-Matching Module (ACMM) that preserves the content structure well without unpleasant artifacts. First, our method uses global attention covariance matching to match the global information of style features with content features, thereby obtaining pleasing stylized images. Then, to enable the model to better match the global statistics, a histogram loss is introduced to improve the saturation and stability of the resulting color. Our method can preserve the content structure; so that appearance transfer can be achieved with simple adjustments to the model. The effectiveness of the proposed method is demonstrated through qualitative and quantitative experiments with comparisons with some state-of-the-art arbitrary style transfer methods.

Community and identity in environmental activism on Twitter: A discourse-based approach

Online communities play an integral role in understanding environmental activist identities. Using #climatestrikeonline tweets as a case study we discuss the benefits of applying the framework of digital pragmatics (under the umbrella of discourse analysis) to study the repositories of online media texts that share the attributes of both interpersonal and mass communication (Koteyko, Nerlich, and Hellsten 2015). Our analysis draws on two arguments central to discourse-based approaches: (1) that social meanings must be analysed across different modes (e.g., by including visuals) and (2) that analysis of digital artefacts needs to consider both their content features and the contexts in which they emerge. We demonstrate how using digital pragmatics to study networked communication about climate change can help us understand how engagement and collaboration are achieved in online communities of practice.

Advanced intelligent health advice with informative summaries to facilitate treatment decision-making

PurposeWhether automatically generated summaries of health social media can assist users in appropriately managing their diseases and ensuring better communication with health professionals becomes an important issue. This paper aims to develop a novel deep learning-based summarization approach for obtaining the most informative summaries from online patient reviews accurately and effectively.Design/methodology/approachThis paper proposes a framework to generate summaries that integrates a domain-specific pre-trained embedding model and a deep neural extractive summary approach by considering content features, text sentiment, review influence and readability features. Representative health-related summaries were identified, and user judgements were analysed.FindingsExperimental results on the three real-world health forum data sets indicate that awarding sentences without incorporating all the adopted features leads to declining summarization performance. The proposed summarizer significantly outperformed the comparison baseline. User judgement through the questionnaire provides realistic and concrete evidence of crucial features that remarkably influence patient forum review summaries.Originality/valueThis study contributes to health analytics and management literature by exploring users’ expressions and opinions through the health deep learning summarization model. The research also developed an innovative mindset to design summarization weighting methods from user-created content on health topics.

'Oh yes, that is also reflection'-Using discursive psychology to describe how GP registrars construct reflection.

Learners in medical education generally perceive that reflection is important, but they also find that reflection is not always valuable or practically applicable. We address the gap between the potential benefits of reflection and its practical implementation in medical education. We examined the perspective of Dutch GP registrars who (must) reflect for their GP specialty training to understand their participant perspective on reflection. Our aim is stimulating alignment between reflective activities that occur in a medical curriculum and the ideals of reflection as a valuable educational activity. We conducted, video-recorded and transcribed seven focus group sessions with GP registrars in 2021 across two Dutch GP educational programmes. We used discursive psychology to analyse the focus group data by focusing on 'assessments of reflection'. We analysed their discursive features (how something was said) and content features (what was said) and related these to each other to understand how GP registrars construct reflection. Participants constructed reflection with nuance; they combined negative and positive assessments that displayed varied orientations to reflection. First, their combined assessments showed complex orientations to norms and experiences with reflecting in practice and that these are not simply negative or positive. Second, GP registrars constructed reflection as a negotiable topic and showed how reflection and its value can be variably understood. Third, through combined assessments, they displayed an orientation to the integration of reflection with other educational tasks, which impacts its value. Generally, GP registrars speak positively about reflection, but the value of reflection partly depends on its proper integration with other educational tasks. When meaningful integration fails, activities to stimulate reflection can overshoot their own goal and hamper learner motivation to reflect. Developing a healthy 'reflection culture' could mitigate some challenges. Therein, reflection is treated as important while learners also have adequate autonomy.

Developing a Digital Health Intervention for Conversation Skills After Brain Injury (convers-ABI-lity) Using a Collaborative Approach: Mixed Methods Study.

People with acquired brain injury (ABI) experience communication breakdown in everyday interactions many years after injury, negatively impacting social and vocational relationships. Communication partner training (CPT) is a recommended intervention approach in communication rehabilitation after ABI. Access to long-term services is essential, both in rural and remote locations. Digital health has potential to overcome the challenges of travel and improve cost efficiencies, processes, and clinical outcomes. We aimed to collaboratively develop a novel, multimodal web-based CPT intervention (convers-ABI-lity) with key stakeholders and evaluate its feasibility for improving conversation skills after brain injury. This mixed methods study consisted of 3 key stages guided by the Integrate, Design, Assess, and Share (IDEAS) framework for developing effective digital health interventions. Stage 1 included the integration of current end-user needs and perspectives with key treatment and theoretical components of existing evidence-based interventions, TBI Express and TBIconneCT. Stage 2 included the iterative design of convers-ABI-lity with feedback from end-user interviews (n=22) analyzed using content analysis. Participants were individuals with ABI, family members, health professionals, and paid support workers. Stage 3 included the evaluation of the feasibility through a proof-of-concept study (n=3). A total of 3 dyads (a person with ABI and their communication partner [CP]) completed 7 weeks of convers-ABI-lity, guided by a clinician. The outcome measures included blinded ratings of conversation samples and self-report measures. We analyzed postintervention participant interviews using content analysis to inform further intervention refinement and development. Collaborative and iterative design and development during stages 1 and 2 resulted in the development of convers-ABI-lity. Results in stage 3 indicated positive changes in the blinded ratings of conversation samples for the participants with traumatic brain injury and their CPs. Statistically reliable positive changes were also observed in the self-report measures of social communication skills and quality of life. Intervention participants endorsed aspects of convers-ABI-lity, such as its complementary nature, self-guided web-based modules, clinician sessions, engaging content, and novel features. They reported the intervention to be relevant to their personal experience with cognitive-communication disorders. This study presents the outcome of using the IDEAS framework to guide the development of a web-based multimodal CPT intervention with input from key stakeholders. The results indicate promising outcomes for improving the conversation skills of people with ABI and their CPs. Further evaluation of intervention effectiveness and efficacy using a larger sample size is required.

Overlooked advantages of interactive book reading in early childhood? A systematic review and research agenda

Previous reviews of the nature and consequences of adult-child book reading have focused on seeking impacts of interactive reading on the acquisition of vocabulary and emergent literacy skills. In this systematic review we examined to what extent there has been systematic study of the effects of interactive reading on four less frequently studied developmental outcomes important to children's academic and life prospects: socio-emotional and socio-cognitive (SEL) skills, narrative skills, grammar, and world knowledge. We identified 67 studies of interactive reading that met the inclusion criteria and that examined the targeted outcomes, using either experimental, quasi-experimental, correlational, or single-group intervention methods. We found that studies of effects on grammar and world knowledge outcomes were very sparsely represented; though narrative was often studied as an outcome, the wide variation in conceptualizing and assessing the construct hampered any clear conclusion about book-reading effects. The most robust research strand focused on SEL skill outcomes, though here too the outcome assessments varied widely. We speculate that better instrumented approaches to assessing vocabulary and emergent literacy have led to the persistent emphasis on these domains, despite robust evidence of only modest associations, and argue that work to develop sound shared measures of narrative and SEL skills would enable cross-study comparison and the accumulation of findings. In addition, we note that the various studies implicated different explanatory principles for the value of reading with children: specific interactional features (open-ended questions, following the child's lead, expanding child utterances) or content features (emotion-enhanced books, talk about mental states, science topics), raising another topic for more focused study in the future.

Study on the penetration capability of GPR for the steel-fibre reinforced concrete (SFRC) segment based on numerical simulations and model test

The SFRC segment is gaining attention in shield tunnels due to their better mechanical properties. However, the existence of steel fibres poses a greater difficulty when attempting to utilize ground penetrating radar (GPR) for nondestructive quality inspection compared to conventional reinforced concrete segments. This paper presented a refined numerical model of SFRC segments with gprMax software, to investigate the penetration characteristics of GPR. The numerical model incorporated four different steel fibre contents, namely 0%, 0.5%, 2.5%, and 5%. The model also included an internal void and a surface metal plate to compare and analyze the waveform characteristics of GPR with the normal sections of the segment. The orthogonal test of numerical simulation investigates the imaging characteristics, power attenuation patterns, and imaging features of three different GPR frequency gradients: 200 MHz, 500 MHz, and 1000 MHz. This analysis helps in selecting the appropriate detection frequency based on the observed energy attenuation patterns and imaging characteristics. Then, the model test was conducted at the selected frequency to study the penetration performance of GPR. The research results indicate that the numerical model established in this paper demonstrates good effectiveness in studying the waveform characteristics of steel fibre-reinforced concrete under various conditions. The numerical model established in this paper realized the study of the penetration characteristics and imaging features of different steel fibre contents, GPR frequencies, and detection targets. Analysis of waveform characteristics, power attenuation, and imaging results indicates that GPR at 500 MHz exhibits better detection performance for SFRC segments. The results of the numerical simulation were verified through model tests of real SFRC segments, demonstrating that 500 MHz has good penetration performance for SFRC segments. This paper also proposed a calculation method for equivalent relative dielectric constant (ERDC) based on the model test results and validated its rationality through the analysis of numerical simulation results and real GPR waveforms.