Digital Age Research Articles

Systematic Analysis of Image Restoration Methods Based on Deep Learning

In today's digital age, people often use images to convey information. However, during the process of sending images, they can become damaged for various reasons, causing the images to lose their original meaning. In such cases, image repair is necessary to restore the damaged areas to their original, undamaged appearance. Traditional image repair methods often struggle to produce effective results for highly damaged images. However, image repair using deep learning techniques can address these challenges effectively. This paper will detail the impact of image repair on Convolutional Neural Networks (CNN), Recurrent Neural Networks (RNN), Long Short-Term Memory networks (LSTM), Convolutional Recurrent Neural Networks (CRNN), and other models, as well as the advantages and disadvantages of each approach. From the data, it is evident that combining multiple models for image repair is the most effective method. This approach reduces the consumption of hardware resources and time required for image repair, thereby improving the overall efficiency of the process.

Research on Key Technologies of Spatial Domain Image Steganography and Analysis of Typical Applications

In the digital age, secure storage and communication of information are crucial aspects of everyday life, drawing significant global interest. Steganography serves as a pivotal method for concealing private information within various media forms—such as images, videos, and text—enabling secure information transmission. This paper delineates the distinctions between information hiding and encryption and delves into image steganography. The focus here is on spatial-based image steganography techniques, which are broadly categorized into traditional and deep learning-based methods. Traditional methods rely on modifications to the pixel values of the host image, often resulting in minor but detectable changes if not carefully managed. On the other hand, deep learning-based methods leverage neural networks to learn how to encode data in an image in a way that is much harder to detect. A comprehensive performance analysis of these techniques is provided, complete with comparative tables to aid in clarity and reference. Additionally, this paper aims to guide researchers by charting current trends in the field and suggesting future research directions. By exploring these advanced techniques, the paper contributes to the broader discourse on enhancing the security and efficacy of steganographic practices.

Research on English Online Teaching Model Based on Association Rules Driven by Big Data

In today’s information age, big data has become an indispensable and important resource in various fields, and the education sector is no exception. With the explosive growth of educational data, how to effectively mine and utilize this data to optimize the education and teaching process has become a focus of attention for educators and researchers. Among them, association rule mining, as an important data mining technique, is increasingly widely used in the field of education. This investigation delves into the deployment of association rule mining within the framework of English online teaching models, capitalizing on the burgeoning domain of big data. In the era of exponentially advancing information technology, big data has crystallized as an integral component for educational enhancement in both pedagogical quality and methodologies. Initially, this paper dissects a spectrum of extant teaching paradigms propelled by big data analytics. The discourse then pivots to scrutinize the contemporary landscape and the evolution of English online pedagogy. Employing association rule analysis, the study excavates a trove of significant patterns and linkages from voluminous datasets of online educational activities. The insights gleaned serve as a compass for refining instructional strategies and judiciously distributing educational resources. The empirical evidence underscores the proposition that granular examination of student engagement metrics and scholastic achievement empowers educators to tailor bespoke educational trajectories, thereby amplifying pedagogical efficacy and enriching the academic voyage. Beyond furnishing an avant-garde outlook on English online instruction, the findings proffer a substantive benchmark for e-pedagogy across diverse academic disciplines.

Examining the Role of School Librarians in Teaching Young Children to Detect and Avoid Misinformation

This study investigates the imperative for implementing an informational literacy curriculum in K-5 school libraries to equip students with essential skills for detecting and avoiding misinformation. Using a mixed-methods approach, data were collected from 141 school librarians across the United States. Quantitative analysis revealed significant gaps in information literacy instruction frequency and resource availability. Qualitative analysis identified four overarching themes: Awareness, Identification, Resources, and Risks/Harm. Together these results highlight the pressing need for curriculum development in this area, emphasizing critical thinking skills through age-appropriate resources. The findings underscore the importance of advocating for dedicated instructional time and the creation of tailored teaching materials to empower students as discerning consumers and responsible citizens. This research contributes valuable insights to the fields of school libraries and information literacy, informing future initiatives aimed at enhancing students' ability to navigate the complexities of the digital age.

Genesis of Street Photography in the Context of the Specificity of Digital Age

The purpose of the article is to reveal the peculiarities of the development of the genre of street photography in the context of the digitalisation trend. Research methodology. The logical-analytical, subject-analytical, system-analytical, typological and historical-cultural method, as well as the method of cultural analysis, were applied in order to comprehensively and objectively study the problems of the development of the genre of street photography. Scientific novelty. The genre of street photography is studied through the prism of the features of digital photography; the influence of surrealism, documentary cinema and humanistic tendencies of photo art on the genre of street photography is analysed; the development of the genre of street photography is traced in historical retrospect and at the present stage in the context of the digitalisation trend; little-known foreign language sources of a cultural nature were introduced into scientific circulation. Conclusions. The main characteristics of digital photography are plasticity (the ability to integrate with other media, close connections and interactions between the camera, mobile phones and social networks in the context of the photo sharing process) and the ubiquity of mobile devices (the ability to easily take a photo with a mobile camera), which the specifics of the creative thinking of a modern person and affects the transformation of the genre of street photography. The study found that the main factors influencing the development of street photography in the digital age are: the emergence of smartphones, social media and online sharing, mirrorless cameras and additional functions, artificial intelligence and computational photography. The ubiquity of digital devices and their relationship with various media significantly transforms the genre, which throughout its history has been characterised by a significant reaction to internal (documentary style, surrealism, humanism) and external interventions (for example, consumer culture, popularisation of other genres of photography, lack of control). At the current stage of the development of the genre of street photography, the main influencing factor is the ubiquity of digital photography – access to the camera and urban space create prerequisites for creativity in the genre of street photography, which gradually leads to the levelling of boundaries between professional and amateur photography. The gravitation of the genre of street photography to documentary or art is determined by the author's approach of a particular photographer, the style he follows, the specifics of the environment and technical means. Thanks to the huge amount of photo equipment, the digital age is changing street photography, creating new trends and influencing the organic development of traditional features of the genre, and its adaptive nature allows us to talk about further transformational processes, in accordance with the development of the socio-cultural space.

Pre-service foreign language teachers’ TPACK preparation for technology integration: what are the profiles and key drivers?

ABSTRACT Technological Pedagogical and Content Knowledge (TPACK) denotes teachers’ professional knowledge to teach specific subjects in the age of information and communication technology. Though the TPACK framework has received extensive research attention in the educational technology field, little effort has been devoted to the profiles of TPACK and technology integration from an intraindividual perspective. Also, the role of TPACK in facilitating technology integration needs more comprehensive exploration before it offers greater theoretical contributions to directing foreign language teacher education. This study explored the profiles of TPACK and technology integration intention using latent profile analysis (LPA) with a sample of 474 pre-service Chinese-as-a-foreign-language (CFL) teachers. The roles of each TPACK component in facilitating technology integration intentions were also examined based on comparative structural equation modelling (SEM) analyses that account for the integrative and transformative views of TPACK. The results provided both person-centred and variable-centred evidence on the contribution of TPACK in preparing teachers’ technology integration. The importance of technology-related knowledge in fostering TPACK has been highlighted, while TK and TPCK were found to be essential dimensions that influenced teachers’ technology integration intention. The findings offer significant implications for future language teacher education to promote technology-integrated instruction through TPACK preparation.

Comparative Analysis of Blink Rates During Printed and On-Screen Reading Across Varying Screen Sizes

Objective: To compare the blink rates during resting periods and while engaging in printed and on-screen reading across different digital screen dimensions.Material and Methods: This study involved thirty-two university students with normal vision, who were recorded during a 3-minute conversation to establish baseline blink rates and subsequently during four reading conditions. Participants read four passages under different conditions: printed text, smartphone, tablet, and computer screens. Video recordings were then analysed to quantify blink rates (blinks per minute, bpm) for each condition.Results: Blink rates significantly decreased in all reading scenarios compared to the baseline resting condition (p-value<0.05). Analysis via repeated measures ANOVA demonstrated significant differences in blink rates across all reading conditions (p-value<0.01). Pairwise comparisons revealed that blink rates during smartphone reading were notably lower than printed text, tablets, and computers (p-value<0.05). Conversely, blink rates exhibited no significant differences between printed text and tablet, printed text and computer, and computer and tablet readings (p-value>0.05).Conclusion: The study reveals a consistent decrease in blink rates during various reading conditions with different digital screens compared to resting states, highlighting the influence of visual engagement on ocular behaviour. Reading with a smartphone has decreased blink rates, which may affect eye health and device use. Understanding these dynamicscan guide ergonomic design to reduce visual discomfort from digital screen use, supporting healthy reading habits in the digital age.

The present and future of child sexual abuse on the metaverse: recommendations for an innovative approach to law enforcement responses

Purpose The purpose of this study is twofold: (1) to diagnose and analyze the current state of child sexual violence in the Metaverse through thematic analysis, identifying patterns and empirically diagnosing issues and (2) to enhance cybercrime investigation capabilities and public safety training in Metaverse investigations in the future. Design/methodology/approach By using thematic analysis, the study examines online child sexual violence victimization cases in the Metaverse, collecting data through keyword searches in newspapers and court records. Research limitations/implications This study provides detailed policy recommendations for building trust between the government and citizens involved in the digital age. Originality/value The research endeavors harbor a dual focus: first, to meticulously dissect and comprehend the prevalent landscape of child sexual violence within the intricate realms of the Metaverse. Through rigorous thematic analysis, the authors endeavor to unearth underlying patterns, diagnose empirical realities and illuminate the pressing issues at hand. Second, the authors aspire to fortify the arsenal of cybercrime investigation techniques, bolstering the capacity for future Metaverse inquiries. Using thematic analysis, the study meticulously scrutinizes a dozen cases of online child sexual violence, meticulously gathering data from diverse sources such as newspapers and court records. The implications of the research extend far beyond academia, offering concrete policy recommendations to safeguard vulnerable denizens of the Metaverse.

College students’ attitudes & privacy literacy knowledge on TikTok

This research explores the privacy literacy and attitudes of college students towards TikTok, a platform deeply embedded in their daily social interactions. With the growing concerns over data privacy, TikTok’s rising influence, and state-level actions such as Florida State University’s ban on its use, this study seeks to fill a critical gap in understanding how undergraduate students engage with and manage their privacy on social media. This research analyzes the relation between privacy and behavior among students, studying, for instance, how well they are aware of risks about their privacy context and how it would change their behavior on TikTok. Also, the study examines how students responded to the university's policy on the ban as well as how they perceived TikTok's privacy settings. In order to provide an overview of privacy literacy levels among young students, the study uses a mix of quantitative (Survey) and qualitative (Interview) approaches. Lastly, it uses the Theory of Information Worlds (Burnett & Jaeger, 2011) to conceptualize the attitude toward privacy derived from social norms, information behavior, and interactions within the same boundaries . Initial findings from a pilot study suggest skepticism about the effectiveness of institutional policies, with limited changes in students’ use of TikTok despite the university’s ban. The full study aims to deepen our understanding of these behaviors and contribute to the broader discourse on privacy in the digital age.

“Leaving no one behind”: digital empathy and inclusive media literacy education for young adults on the autism spectrum

The paper advocates for the necessity of inclusive media literacy education (MLE) and equal opportunities for young adults with autism spectrum disorder (ASD), which is in alignment with the United Nations Convention on the Rights of Persons with Disabilities (UNCRPD) 2008 and the Sustainable Development Goal 4 Quality Education (SDG, 2030). It underscores the commitment to ‘leaving no one behind’, a core tenet of the SDGs, by focusing on developing digital empathy and inclusive MLE for young adults with ASD in the digital age. The study aims to empower young adults with ASD in Chennai, India, with media literacy and digital empathy through a one-day hands-on workshop and to assess the impact of this educational intervention on their understanding and application of media literacy in their daily lives. The paper employs a mixed-method approach that integrates experimental-qualitative research and the data is analysed using ‘qualitative reflexive’ thematic analysis. The study’s findings demonstrate significant improvements in the participants’ abilities to discern fake news, learn digital empathy and cybersecurity by engaging responsibly with digital media, and include MLE in their academic curriculum. The paper suggests that such educational interventions can enhance digital empathy and media literacy among young adults with ASD.

Emotional Marketing, Customer Retention, and Brand Loyalty in Vietnam’s Retail Sector: Unveiling the Moderating Impact of Digital Innovativeness

This study investigates the relationship between emotional marketing, brand loyalty, and customer retention in Vietnam’s retail sector, while examining the moderating role of digital innovativeness, comprising personal and brand innovativeness. A conceptual model is developed and empirically tested using a sample of 533 Vietnamese retail consumers. The model incorporates emotional marketing as the main predictor, brand loyalty as the mediator, customer retention as the outcome, and digital innovativeness as the moderator. Relevant determinants of brand loyalty, such as customer satisfaction, perceived value, emotional attachment, and brand identity, are included as control variables. The data is analyzed using structural equation modeling. The results reveal that emotional marketing has a significant positive impact on brand loyalty, which in turn leads to higher customer retention. Digital innovativeness is found to positively moderate the relationship between emotional marketing and brand loyalty. The study highlights the importance of leveraging emotional marketing strategies and fostering digital innovativeness to build strong emotional connections, brand loyalty, and long-term customer retention in the Vietnamese retail market. This research contributes to the understanding of emotional marketing’s impact on brand loyalty and customer retention in the context of Vietnam’s retail sector, while uniquely exploring the moderating effect of digital innovativeness. The findings provide valuable insights for retailers seeking to optimize their marketing strategies and adapt to the evolving needs of Vietnamese consumers in the digital age.

Deep learning to combat knee osteoarthritis and severity assessment by using CNN-based classification

BackgroundIn today’s digital age, various diseases drastically reduce people’s quality of life. Arthritis is one amongst the most common and debilitating maladies. Osteoarthritis affects several joints, including the hands, knees, spine, and hips. This study focuses on the medical disorder underlying Knee Osteoarthritis (KOA) which severely impairs people’s quality of life. KOA is characterised by restricted mobility, stiffness, and terrible pain and can be caused by a range of factors such as ageing, obesity, and traumas. This degenerative disorder leads to progressive wear and tear of the knee joint.MethodsTo combat arthritis in the kneecap, this study employs a 12-layer Convolutional Neural Network (CNN) to reach deep learning capabilities. A collection of data from the Osteoarthritis Initiative (OAI) is used to classify KOA. Through the use of medical image processing; the study ascertains whether an individual has this ailment. A sophisticated CNN architecture created especially for binary classification and KOA severity utilising deep learning algorithms is the main component of this work.ResultsThe cross-entropy loss function is an important component of the model’s laborious design that classifies data into two groups. The remaining section uses the Kellgren-Lawrence (KL) grade to classify the disease’s severity. In the binary classification, the proposed algorithm outperforms previous methods with an accuracy rate of 92.3%, and in the multiclassification, its accuracy rate is 78.4% which is superior to the previous findings.ConclusionLooking ahead, the research broadens the scope of this work by gathering information from various sources and using these methods on a wider range of datasets and situations. The potential for major advancements in the field of osteoarthritis detection and classification is highlighted by this forward-looking approach. Furthermore, this method reduces the intervention of medical practitioners and ultimately results in accurate diagnosis.Clinical trial numberNot applicable.

Applying the Constructive Journalism Approach to Combat Chinese Information Disorder in the Digital Age

Applying the Constructive Journalism Approach to Combat Chinese Information Disorder in the Digital Age

Physiotherapy in the digital age: A narrative review of the paradigm shift driven by the integration of artificial intelligence and machine learning

Abstract: A variety of physical impairments and functional restrictions are assessed and treated in the practice of physiotherapy. Subjective measures, rater variability, and restricted access to high-quality care are some of the unavoidable problems that contemporary physical therapy practice approaches must overcome. In light of these challenges, cutting-edge technologies such as artificial intelligence (AI) and machine learning (ML) are demonstrating remarkable efficacy in tackling these issues head-on. The focus of this review is to explore how the integration of AI and ML might change physical therapy practice and education in the age of digital communication. It delves into the challenges accompanying this integration and considers future prospects in this domain. A literature search was conducted using data base PubMed, Google Scholar, Web of Science, and Scopus with keywords such as ‘physiotherapy’, ‘artificial intelligence’, and ‘machine learning’, limited to English articles from 2014 to 2024. Results were imported into reference management software, duplicates removed, and relevant articles were screened and assessed for inclusion, with reasons for exclusion documented. Emerging technologies like AI and ML use algorithms to examine patient data and make automatic decisions, enhancing areas such as virtual reality therapy (VR), tele-rehabilitation, clinical decision support, individualized rehabilitation and physical function evaluation. These advance technologies optimize physical therapy and improve outcomes, but further research is needed to address obstacles like bias and data privacy to ensure responsible implementation. AI and ML can revolutionize physical therapy by improving therapy precision, patient monitoring, optimization and individualized therapy plan. However, it’s crucial for physiotherapists to balance technological advancements with compassionate, patient-centred approach.

UDIS: Enhancing Collaborative Filtering with Fusion of Dimensionality Reduction and Semantic Similarity

In the era of vast information, individuals are immersed in choices when purchasing goods and services. Recommender systems (RS) have emerged as vital tools to navigate these excess options. However, these systems encounter challenges like data sparsity, impairing their effectiveness. This paper proposes a novel approach to address this issue and enhance RS performance. By integrating user demographic data, singular value decomposition (SVD) clustering, and semantic similarity in collaborative filtering (CF), we introduce the UDIS method. This method amalgamates four prediction types—user-based CF (U), demographic-similarity-based (D), item-based CF (I), and semantic-similarity-based (S). UDIS generates separate predictions for each category and evaluates four different merging techniques—the average, max, weighted sum, and Shambour methods—to integrate these predictions. Among these, the average method proved most effective, offering a balanced approach that significantly improved precision and accuracy on the MovieLens dataset compared to alternative methods.

Advances of Triboelectric and Piezoelectric Nanogenerators toward Continuous Monitoring and Multimodal Applications in the New Era

Abstract Benefiting from the widespread potential applications in the era of Internet of Thing (IoT) and metaverse, triboelectric and piezoelectric nanogenerators have attracted considerably increasing attention. Their outstanding characteristics, such as self-powered ability, high output performance, integration compatibility, cost effectiveness, simple configurations and versatile operation modes, could effectively expand the lifetime of vastly distributed wearable, implantable and environmental devices, eventually achieving self-sustainable, maintenance-free and reliable systems. However, current triboelectric/piezoelectric based active (i.e., self-powered) sensors still encounter serious bottlenecks in continuous monitoring and multimodal applications due to their intrinsic limitations of monomodal kinetic response and discontinuous transient output. This work systematically summarizes and evaluates the recent research endeavours to addressing the above challenges, with detailed discussions on the challenge origins, designing strategies, device performance and corresponding diverse applications. Finally, conclusions and outlook regarding the research gap in self-powered continuous multimodal monitoring systems are provided, proposing the necessity of future research development in this field.

Analysis of Stakeholder Behavior Adjustment Strategies for Entrepreneurship Education in Higher Education Institutions from the Perspective of Digital Collaboration

Under the background of digital age, this study discusses the behavior debugging strategies of stakeholders in entrepreneurship education in colleges and universities. The research significance is that with the rapid development of information technology, digital collaboration has become an important force to promote the development of entrepreneurship education in colleges and universities. Through questionnaire survey and data analysis, it is found that college students' cognitive interest in innovation and entrepreneurship fluctuates regularly with time, and college entrepreneurship education should adjust curriculum design and teaching methods according to this cognitive law. The research suggests that colleges and universities should integrate the resources and advantages of teachers, students, parents, businesses, financial institutions and communities, strengthen cooperation through digital platforms, and optimize the implementation path of entrepreneurship education. At the same time, the government should provide policy support, narrow the digital gap between universities, build a cooperation platform, and promote data security and privacy protection. These strategies aim to improve the quality of education and cultivate innovative entrepreneurial talents to meet the needs of the digital age.

Health Librarians' Perceptions and Utilization of ChatGPT for Digital Literacy in Libraries

Libraries are adapting to the digital age, with health librarians utilizing AI technologies like ChatGPT to support patrons' digital literacy (Chen, 2023). Although prior research has explored AI's role in libraries, little is known about how health librarians leverage ChatGPT, especially regarding health information seeking behavior. This study investigates health librarians' experiences and perspectives on integrating ChatGPT into digital literacy services. Through semi-structured interviews, thematic analysis reveals innovative applications of ChatGPT, such as real-time Q&A sessions and personalized learning experiences. Despite technical challenges like accuracy and reliability, librarians implement quality control measures and continuously update ChatGPT's knowledge base. The study revealed ChatGPT's positive impact on patrons, encouraging improved understanding of health information and confidence in digital resource navigation. Despite challenges, health librarians acknowledge ChatGPT's potential to enhance digital literacy services. Recommendations include addressing technical issues, providing librarian training, and improving user engagement strategies (Yamson, 2023). Overall, this research shows ChatGPT's role in advancing digital literacy within libraries, providing perspectives into its effective integration and potential improvements.

Path of career planning and employment strategy based on deep learning in the information age.

With the improvement of education level and the expansion of higher education, more students can have the opportunities to obtain better education, and the pressure of employment competition is also increasing. How to improve students' employment competitiveness, comprehensive quality and the ability to explore paths for career planning and employment strategies has become a common concern in today's society. Under the background of today's informatization, the paths of career planning and employment strategies are becoming more and more informatized. The support of Internet is essential for obtaining more employment information. As a representative product of the information age, deep learning provides people with a better path. This paper conducts an in-depth study of the career planning and employment strategy paths based on deep learning in the information age. Research has shown that in the current information age, deep learning through career planning and employment strategy paths can help students solve the main problems they face in career planning education and better meet the needs of today's society. Career awareness increased by 35% and self-improvement by 15%. This indicated that in the information age, career planning and employment strategies based on deep learning are a way to conform to the trend of the times, which can better help college students improve their understanding, promote employment, and promote self-development.This study combines quantitative and qualitative methods, collects data through questionnaires, and uses deep learning model for analysis. Control group and experimental group were set up to evaluate the effect of career planning education. Descriptive statistics and correlation analysis were used to ensure the accuracy and reliability of the results.

A study on media and information and traffic convergence in the digital age on consumption

The digital age is the age of productivity innovation. It is the era of industrial transformation and market development to satisfy the public's eyeball economy. Under traditional productivity, new products are often produced and introduced to the market and the public accepts and adapts to the new products, and those products that are not accepted by the public will be eliminated by the market. Now, in the emerging digital era, through data and its analysis, the product and market have begun to analyse the user and market pain points, according to user data to design and develop products for the needs of the user to enjoy at the same time for the data and traffic payment. This is "information consumption" and "data consumption". Poor information is the tool to make money in the current era. How to grasp the information and data of the user group and consumer demand becomes the key. Emerging media is the key to unlocking users' needs. The purpose of this study is to find the role of this key in the integration of information and traffic into consumption. The significance of this study is to deduce the relationship between media and the convergence of information and traffic to consumption in the digital age by analysing the case of the company. The result of this study is that the digital era has created advanced productivity, and the development of productivity has led to innovations in the means and tools of the media industry, which have contributed to the development of user needs. The media is the key to creating and capturing the needs of user groups. It is also the cornerstone for creating "information consumption" and "traffic consumption".