Multimedia Content Research Articles

The Use of Digital Smart Boards as a Means of Supporting TPACK-Based Interactive Learning

A new challenge in the world of education must be able to increase the attractiveness of learning by developing technology-based learning media with digital smart boards. This study aims to observe learning devices and models that use Smart Board Digital as a TPACK-based learning tool on learning quality. A type of research that uses data in the form of numbers to analyze and produce empirically measurable information. In this data collection study, the researcher used observation, questionnaire, and documentation techniques. The analysis techniques used are T-test and F-test. TPACK-based learning tools using Digital Smart Board have an effect on the quality of learning. There is a significant influence between the development of a learning model using TPACK-based Digital Smart Board on the quality of learning at SMPIT Mutiara Cendekia Lubuklinggau. Interactive Whiteboard revolutionizes the classroom experience by allowing teachers to display a variety of multimedia content such as videos, images, and interactive simulations directly on a large touch-sensitive screen that highly motivates students to learn. An innovative media that is able to attract students’ attention to be actively involved in learning so that students’ grades in learning can be better. One of them is the smart board learning media.

Development of Multimedia Teaching Content for Basketball in High School

Background and Aim: In the continuous development of information technology, the global education sector has been greatly impacted by the globalization of information, the application of modern information technology can be seen everywhere, which will profoundly change education. Modern information technology with network and multimedia technology as the core has been applied in physical education teaching in schools and universities. It is necessary to reform and upgrade the traditional education mode and develop multimedia teaching methods. Therefore, this research was to develop multimedia teaching content for basketball in high school, to promote the use of multimedia technology in physical education teaching. Materials and Methods: The survey included 516 students and 35 teachers from 10 high schools in Guangzhou, questionnaire was used to investigate the current situation of basketball teaching. Then, 7 teachers were interviewed to consult the problem solutions, and the indicator contents of multimedia teaching content for basketball in high school was constructed by literature review and content analysis. Through 19 Delphi experts’ consensus, multimedia teaching content for basketball in high school was established. Finally, 9 experts were invited to confirm the developed multimedia teaching content by the Connoisseurship method. In this research, mean, standard deviation and coefficient of variation were used to analyze the data. Results: After two rounds of Delphi method investigation, statistics, and modification, there are 92 indicators suitable for using multimedia in high school basketball teaching content. The content of high school multimedia basketball teaching is designed and includes the origin and development of basketball, sports injuries, and prevention, basic movement of a basketball player, dribble technique, one-handed marching shot, basic movement of a basketball player, basic basketball rules, shoot technique, pass technique, defend technique, breakthrough technique, advanced dribbling, steal technique, zone cooperation, pick and roll and defense, attacking match, fast break and defense, one-on-one check, offensive zone defense. Conclusion: The multimedia teaching content for basketball high school in Guangzhou was effective and appropriate, and can be integrated into the teaching plan.

Smart Caption: Intelligent Image Description Using Transformer Decoder

The need for automated image description systems has grown significantly with the rise of multimedia content across diverse domains such as social media, digital libraries, and accessibility technologies. Smart Caption presents a novel approach for generating intelligent and context-aware image descriptions by utilizing a combination of Vision Transformers (ViTs) and Natural Language Processing (NLP) Transformer decoders. Unlike traditional convolution-based methods, Vision Transformers treat images as sequences of patches, enabling them to capture global image features more effectively. These extracted visual features are then processed by a Transformer-based decoder to produce coherent and contextually appropriate captions, bridging the gap between image recognition and natural language generation. Our approach focuses on leveraging the attention mechanisms inherent in both Vision and NLP Transformers to enhance the quality of image descriptions. The ViT architecture is designed to focus on relevant regions within an image, while the NLP Transformer decoder is adept at generating fluent and detailed descriptions by attending to the most significant visual features. This two-stage process improves the precision of object detection, relationship understanding, and scene context in generated captions. Experimental results demonstrate that Smart Caption out performs traditional methods in terms of accuracy, contextual relevance, and fluency, marking a significant step forward in the field of automated image captioning. Through this research, we aim to provide a scalable, efficient, and intelligent solution for image description, with potential applications in areas such as accessibility tools for visually impaired users, digital content indexing, and automated content generation. Our findings highlight the strengths of transformer-based models in bridging vision and language tasks, offering promising directions for future research in multimodal AI..

Advancing language learning: The impact and challenges of Computer-Assisted Language Learning (CALL)

Abstract. Computer-Assisted Language Learning (CALL) represents a transformative approach in modern education, integrating technology to enhance language acquisition effectively. This comprehensive review examines the various dimensions of CALL, focusing on its deployment through interactive software, online courses, mobile applications, and the accompanying challenges. Quantitative analyses reveal significant improvements in learner engagement and cognitive load management due to multimedia and interactive content. Moreover, the adaptability of CALL to cater to individual learning needs through personalized and adaptive learning systems demonstrates a superior proficiency acquisition rate. Despite these advancements, CALL implementation faces substantial barriers including technological limitations, the need for extensive teacher training, and concerns regarding data privacy and security. This article assesses the statistical impact of these elements on language learning outcomes and suggests strategies for overcoming the associated challenges. Through mixed-methods research and longitudinal studies, the effectiveness of CALL platforms is substantiated, highlighting their pivotal role in reshaping language education across diverse demographic and geographic spectrums.

Assessment of Informatics Competency Among Nursing Faculty Members and Its Application in Educating Nursing Students at Abadan Nursing Faculty

Background: Nursing informatics in educational activities can serve as a strategy to bridge the gap between clinical practice and nursing education programs. Objectives: This study aimed to assess the informatics competency of nursing faculty members and its application in educating nursing students at Abadan Nursing Faculty. Methods: This descriptive-analytical research was conducted in 2023 at Abadan Nursing Faculty. The sample consisted of 73 faculty members from the nursing, operating room, and anesthesia departments, who were included in the study through census sampling. Data collection was performed using the standardized Nursing Informatics Competency Assessment Tool (NICAT) and an electronic teaching aids checklist. Data were analyzed using SPSS version 18, with independent t-tests, one-way analysis of variance (ANOVA), and Pearson’s correlation at a significance level of P < 0.05. Results: The mean score of faculty members’ nursing informatics competency at the Nursing Faculty was 110 out of a maximum of 150, placing it within the proficient range. The highest score for nursing informatics competency was related to the informatics literacy dimension (47.65), while the lowest was related to the information management skills dimension (19.54). Information management skills (r = 0.881, P < 0.001), computer literacy (r = 0.871, P < 0.001), and informatics literacy (r = 0.976, P < 0.001) were significantly correlated with nursing informatics competency. Faculty members reported the highest use of multimedia content development (mean score = 4.19) and the lowest use of robotic surgery (mean score = 1.71). Conclusions: Faculty members’ informatics competency was reported to be at a proficient level. However, due to advancements in technology and transformations in nursing care, it seems necessary to improve nursing faculty members’ abilities in all aspects, particularly in the information management skills dimension. It is recommended to hold faculty development programs regarding the integration of technology into the curriculum to elevate the quality of education.

Science in the Language of the Heart: Ukrainian Language and Literature in the New Ukrainiian School as a Driver of STEM Development

The article outlines the pathways for integrating STEM disciplines into the planning of Ukrainian language and literature lessons in secondary education institutions within the framework of the New Ukrainian School. It substantiates the growing need for interdisciplinary approaches that foster the development of core competencies while considering the advantages, potential risks, and limitations of the proposed methods. The emphasis is placed on the importance of combining humanities with natural and mathematical sciences to enhance students' understanding of a holistic worldview, illustrating the need to avoid focusing solely on one aspect of development (so-called «humanitarians» and «technocrats»). The article offers theoretical and practical recommendations for developing STEM projects that engage students in creative literary exploration through applying scientific principles and doctrines. The effective combination of STEM education principles with the field of philology enables the creation of a dynamic and effective educational environment where students perceive the interconnectedness of knowledge, develop a well-rounded intellect, and receive foundational preparation for higher education. Methods of linguistic analysis of scientific texts are discussed, demonstrating how language skills can be enhanced through scientific discourse. To illustrate the material, approximate schemes for planning integrated lessons with specific examples from both linguistic-literary and scientific perspectives are provided. To improve understanding and engagement of modern students, emphasis is placed on using digital tools and platforms that ensure integration, including online resources, interactive modeling, multimedia content and artificial intelligence. The necessity for alignment among educators of various disciplines is evident to ensure a fair assessment of proficiency in the state language and scientific literacy, which is a crucial issue during wartime when language matters become increasingly prominent, alongside scientific and mathematical literacy, for building an intellectually developed country.

A New Encryption Algorithm Utilizing DNA Subsequence Operations for Color Images

The computer network has fundamentally transformed modern interactions, enabling the effortless transmission of multimedia data. However, the openness of these networks necessitates heightened attention to the security and confidentiality of multimedia content. Digital images, being a crucial component of multimedia communications, require robust protection measures, as their security has become a global concern. Traditional color image encryption/decryption algorithms, such as DES, IDEA, and AES, are unsuitable for image encryption due to the diverse storage formats of images, highlighting the urgent need for innovative encryption techniques. Chaos-based cryptosystems have emerged as a prominent research focus due to their properties of randomness, high sensitivity to initial conditions, and unpredictability. These algorithms typically operate in two phases: shuffling and replacement. During the shuffling phase, the positions of the pixels are altered using chaotic sequences or matrix transformations, which are simple to implement and enhance encryption. However, since only the pixel positions are modified and not the pixel values, the encrypted image’s histogram remains identical to the original, making it vulnerable to statistical attacks. In the replacement phase, chaotic sequences alter the pixel values. This research introduces a novel encryption technique for color images (RGB type) based on DNA subsequence operations to secure these images, which often contain critical information, from potential cyber-attacks. The suggested method includes two main components: a high-speed permutation process and adaptive diffusion. When implemented in the MATLAB software environment, the approach yielded promising results, such as NPCR values exceeding 98.9% and UACI values at around 32.9%, demonstrating its effectiveness in key cryptographic parameters. Security analyses, including histograms and Chi-square tests, were initially conducted, with passing Chi-square test outcomes for all channels; the correlation coefficient between adjacent pixels was also calculated. Additionally, entropy values were computed, achieving a minimum entropy of 7.0, indicating a high level of randomness. The method was tested on specific images, such as all-black and all-white images, and evaluated for resistance to noise and occlusion attacks. Finally, a comparison of the proposed algorithm’s NPCR and UAC values with those of existing methods demonstrated its superior performance and suitability.

Designing and Evaluating a Web-Based Training Program for Medical Record Documentation: Insights from a Developing Country Experience

BackgroundThe quality of medical documentation is crucial for enhancing patient care, as accurate records reduce medical errors and improve patient safety. Given the pivotal role of medical records in delivering high-quality healthcare services, effective training in documentation skills is essential. Whence, this study aimed to design and evaluate a web-based training program focused on medical record documentation, specifically for medical students in Iran (West Azerbaijan province, Urmia), but can be easily adapted to other pertinent cases. MethodThis semi-experimental study was conducted in 2023 and comprised three main phases: pre-intervention, intervention, and post-intervention. In the first phase, an online questionnaire assessing knowledge, attitudes, and performance was developed and integrated into the web-based education program. During the second phase, multimedia electronic content was created and made accessible to students for two months. In the final phase, the same online questionnaire was administered to the students again. The study involved 114 medical students from Urmia University of Medical Sciences. Among the 114 medical students (61 externs and 53 interns), 53.4% were male, and 46.6% were female. The data were analyzed using SPSS 16 software. ResultsFollowing the intervention, students’ knowledge scores are seen increase from 76.50 to 86.30, attitudes improved from 79.33 to 85, and performance enhanced from 74.92 to 81.40. Further statistical analysis reveals that the web-based training significantly impacted the knowledge, attitudes, and performance of the medical students regarding documentation, with a p-value less than 0.05. ConclusionThe findings of this specific study indicate that web-based education, supplemented with multimedia content, has led to significant improvements in the knowledge, attitudes, and performance of medical students in medical record documentation. While these positive outcomes suggest that the course characteristics played an important role, further investigation is no doubt needed to establish a direct causal relationship. Ongoing studies are surely recommendable. Nonetheless, implementing such educational approaches appears to be an essential ingredient for enhancing the documentation skills of future healthcare professionals. The study may open educational perspectives and inspire further ad hoc research in nearby domains making use of complex documentation.

The Analysis of Resilientnet-Realtime Disaster Response System

Responding to India's urgent need for effective disaster management, proposed framework ResilientNet, an innovative system leveraging real-time big data processing and advanced AI technologies. ResilientNet gathers diverse multimedia content from a wide range of social media services, including Twitter, Instagram, Facebook, etc., and utilises the GEMINI API, enabling comprehensive analysis and verification. Data is stored in the NEO4J database and visually represented on a user-friendly website dashboard for easy accessibility and insights. This research explores the efficacy of crowdsourced fact- checking, contributing to a novel disaster-focused tweet verification system. ResilientNet's amalgamation of crowdsourcing and AI creates a comprehensive graph of critical metrics and trends, enabling authorities to counter misinformation and direct disaster response efforts efficiently.

Hybrid LSTM and Encoder-Decoder Architecture for Detection of Image and Video Forgeries

This paper introduces a hybrid architecture combining Long Short-Term Memory (LSTM) networks and an encoderdecoder model for the detection and localization of image and video forgeries. The proposed system leverages resampling features and LSTM cells to identify manipulation patterns such as splicing and retouching in multimedia content. By utilizing a combination of spatial and temporal features, the model achieves high precision in detecting forged regions. Extensive testing on diverse datasets demonstrates the robustness of the proposed method.

Kiswahili Translation in Digital Media Platforms: Bridging Language Gaps in the AI Age

Purpose: As digital media platforms continue to proliferate globally, the need for multilingual content in these platforms has become increasingly apparent. Translation of online content is a necessity for netizens and other digital platform users who seek knowledge and information around a myriad of user-generated content on diverse issues and topics. Being a widely spoken language that goes beyond the borders of East Africa, Kiswahili’s significance in bridging linguistic barriers and facilitating communication and information access for Kiswahili speakers is clear. The purpose of this exploratory research paper was to examine the state of Kiswahili as a language of translation through different technologies across varied translation apps and social media platforms such as Facebook, You Tube, Tik Tok and Netflix. Methodology: The study adopted a descriptive research design. Data collection was done through online data mining tools including API access for web scrapping and manual extraction of content through random search engine searches. The data for the study included 10 sentences, 10 videos and 25 specific word forms such as proverbs, spiritual/religious words, similes and cultural words for food, beauty and family ties. Content analysis for both text and multimedia content such as written sentences, social media posts and videos was done. The study analyzed translation outputs of 14 Kiswahili translation apps in order to establish the status and accuracy of these translations. Of key consideration was the role of AI technology in the translation apps and the effect it has on the translated texts across different apps. The challenges and emerging issues facing Kiswahili translation through digital technologies were also explored. Findings: The findings of this study showed that the Apps used for Kiswahili translation have demonstrated great translation accuracy in basic semantic forms, with an average score of 60% accuracy upon random searches and between 10-30% accuracy for cultural forms and idiomatic expressions. Unique Contribution to Theory, Practice and Policy: The study was guided by the Skopos theory by Hans Vermeer (1978) which was complemented by the Relevance Theory by Dan Sperber and Deidre Wilson (1986). These Apps seem to have the feature of interoperability in that they seem to produce the same results suggesting that the AI supported feature in the apps may be interconnecting the apps during translation. The study advocates for more AI integration translation apps as this will help standardize Kiswahili translation corpus.

Get Peace of Mind with Do-It-Yourself Living Wills: The Digitalisation of Medical-Legal Practice and the New Post-Covid 19 Approach

“The automatisation of the core tasks performed by legal practitioners […] is an ongoing and open-ended process” (Schäfke-Zell & Asmussen, 2019, p. 65). “A host of innovative legal-tech companies have entered the market of legal service providers, presently challenging the lawyers’ monopoly over the practice of the law, and ultimately, altering the mode of production in the legal field” (Caserta, 2020, p. 1). Beginning with these assumptions, this study draws on ongoing research on healthcare powers of attorney, living wills, and advance directives (Giordano, 2019, 2021) and will explore the current radical changes and restructuring of modalities of production in medical-legal documents and in the delivery of legal services. The legal websites in the corpus under investigation provide guidance in creating a personal living will according to well-established legal procedures that are pursuant to the laws and regulations of a particular state or country. Living wills and advance directives are signed documents in which the declarants state whether or not they wish to be kept alive using artificial means in the event a doctor declares their death to be imminent. Doctors and medical practitioners are legally bound to follow these directives. Following the increased digitalization of the legal field, these documents are now frequently drafted and completed online, thus embracing the full potential of the new technologies available today. Both verbal and visual rhetoric (Murray, 2014; Sherwin, Feigenson, & Spiesel, 2005) will be investigated to ascertain whether and to what extent digital transformation is redefining the ways in which this legal service is offered, thus promoting greater understanding and wider knowledge of a controversial issue such as making decisions regarding one’s end of life and the choices available among various life-prolonging measures and treatments. The research aims to determine whether the new digital genres can help translate the specific constraints and demands of legal argumentation into new popular, cultural and technological discourse which better appeals to peoples’ emotions and values. The legal sector’s increasing use of digital forms and templates embellished with visual and multimedia content may at once have a commodifying and democratizing effect. Legal meanings and services in the new legal market (Schäfke-Zell & Asmussen, 2019, p. 66) might be better understood and internalized, thus reinforcing and disseminating the emerging vernacular of digital culture along with law, regulations and legal institutes and instruments, which would otherwise be difficult for a layperson to comprehend or accept (Anesa, 2016; Calsamiglia, 2003; Calsamiglia & van Dijk, 2004). In addition to this process of democratization of new media, the Coronavirus pandemic also contributed to changing people’s approach to life (Garzone, 2023) and to living wills, triggered by an increased sense of precariousness of life and imminence of death. English-speaking countries, in particular, have seen a surge in people updating and altering advance directives as a result of the complications caused by the disease; different steps might be taken now, when current documents may be dangerously inadequate. The best ways to update existing texts to the new post-Covid 19 conditions therefore call for thorough investigation.

Empowering Student Transition and Engaging Students Using Actionbound: A Gamified Collaborative Community Learning Platform

Transition to University is a significant milestone for students who are embracing new experiences and challenges. It is particularly vital for international students who have to adapt to a new and different learning environment in the UK. Successful transition and sense of belonging in a new institution lay foundation for students’ academic success. However, transition is a process rather than an event. Accordingly, fostering a collaborative community learning environment and facilitate peer networks and community support becomes critical. It enables social interactions and active learning by engaging students in collaborative group activities, which would in turn support students’ transition to and belonging in a new learning environment. With the advancement of technology, computer-assisted and computer-supported collaborative learning flourished in 21st century. The emergence of mobile digital technology leads to the design of gamification in learning, known as game-based learning or gamified collaborative community learning in order to engage students in fun and interactive activities. ‘Actionbound’ is one of the versatile gamification platforms and mobile apps which can engage students in collaborative community learning with gamified activities. It enables users to create, share and participate in interactive scavenger hunts, tours, games and quizzes. It allows users to design custom challenges, incorporate multimedia content and track players’ progress in real-time. It engages participants to work collaboratively to solve challenges and complete tasks. At UHBS, we have used Actionbound to support the student transition into the University’ learning journey at the start of term. We used scavenger hunt game and quiz functions within Actionbound to direct students to collaborate in teams to solve the challenges and tasks. In this action research, students found Actionbound fun and loved the competitive nature with points and leaderboards. It helped them build network and form friendship. Together, they solved puzzles and tackled challenges which supported their transition and got them prepared for learning in a new environment. Moving forward, as an ongoing action research, we would like to extend the use of Actionbound to term time and in module delivery so to track students’ engagement with the collaborative learning platform and investigate the impact on their academic performance.

Advancing radiology education for medical students: leveraging digital tools and resources.

This study evaluates diverse educational resources to address the gaps in diagnostic radiology education for medical students, aiming to identify tools that enhance theoretical knowledge and practical diagnostic skills. Employing a multi-faceted review, we analyzed digital platforms, academic databases, and social media for resources beneficial to medical students in radiology, assessing their accessibility, content quality, and educational value. Our investigation uncovered a broad spectrum of resources, from foundational platforms to advanced simulation tools, varying in their approach to teaching radiology. Traditional resources provide essential theoretical knowledge, while digital tools, including interactive case studies and multimedia content, offer immersive learning experiences. Notably, resources integrating machine learning and social media facilitate dynamic, peer-to-peer learning and up-to-date case discussions. Despite the minimal current focus on VR, its role in enhancing interactive learning is notable. The diversity in educational tools highlights the evolving nature of radiology education, reflecting a shift towards more engaging and practical learning methodologies. Identifying and integrating a variety of educational resources into radiology education can significantly enhance learning outcomes for medical students, preparing them for the complexities of modern diagnostic radiology with a well-rounded educational approach.

A Compressed Domain Robust Video Watermarking Resists Geometric Attack

The widespread utilization of mobile devices and the proliferation of video content, facilitated by communication networks, has unfortunately led to issues such as data piracy, illegal usage, and unauthorized sharing. To address these challenges, digital watermarking emerges as a crucial tool, serving purposes such as authentication, maintaining integrity, and identifying rightful owners. In the realm of video watermarking, two primary categories exist: watermarking in the compressed domain and watermarking in the uncompressed domain. Compressed domain watermarking involves expedited data processing through partial video decoding, whereas uncompressed domain watermarking requires more time. This article proposes a novel video watermarking methodology designed specifically to withstand geometric attacks. The proposed method aims to dynamically embed watermarks within video content, thereby enhancing resilience against various geometric distortions. Geometric attacks, including scaling, rotation, cropping, and translation, pose significant challenges in digital watermarking and are thus a focal point of this research. The objective is to integrate this approach with complex video coding standards, leveraging compression domain techniques to fortify resistance against geometric attacks. Tests show that the suggested video watermarking system works well. Not only does it excel in safeguarding against geometric attacks, but it also mitigates perceptual quality degradation, thus ensuring a balance between robustness and visual fidelity. As the prevalence of video content continues to grow, robust watermarking techniques like the one presented here play a vital role in preserving intellectual property rights and ensuring the integrity of multimedia content in the digital age.

Toward comprehensive short utterances manipulations detection in videos

AbstractIn a landscape increasingly populated by convincing yet deceptive multimedia content generated through generative adversarial networks, there exists a significant challenge for both human interpretation and machine learning algorithms. This study introduces a shallow learning technique specifically tailored for analyzing visual and auditory components in videos, targeting the lower face region. Our method is optimized for ultra-short video segments (200-600 ms) and employs wavelet scattering transforms for audio and discrete cosine transforms for video. Unlike many approaches, our method excels at these short durations and scales efficiently to longer segments. Experimental results demonstrate high accuracy, achieving 96.83% for 600 ms audio segments and 99.87% for whole video sequences on the FakeAVCeleb and DeepfakeTIMIT datasets. This approach is computationally efficient, making it suitable for real-world applications with constrained resources. The paper also explores the unique challenges of detecting deepfakes in ultra-short sequences and proposes a targeted evaluation strategy for these conditions.

Accessibility Challenges of Using Podcasts and Vodcasts in a South African Distance Learning University

Academic writing presents a range of challenges for students, particularly those enrolled in distance university institutions. These challenges encompass various facets such as understanding citation and referencing, developing a distinctive writer’s voice, mastering academic discourse, paraphrasing, summarising, and adhering to academic conventions. Notably, deficiencies in academic writing skills often trace back to inadequate preparation during high school education, potentially leading to qualification deferment and high dropout rates. To tackle these challenges, podcasts and vodcasts emerged as essential tools to bridge academic gaps, catering to diverse learning styles and offering flexibility beyond traditional teaching methods. However, the efficacy of supplemental multimedia tools warrants exploration, considering uncertainties regarding student acceptance. Thus, this study aimed to identify accessibility challenges, to reduce existing barriers and enhance accessibility in open distant institutions. Utilising qualitative research methodologies, including focus group discussions and literature analysis, data collection was conducted. The study drew upon Moore’s theory of transactional distance and Garrison et al.’s community of inquiry framework to create collaborative online interactions and meaningful lecturer-student engagement, culminating in the construction of new knowledge. Findings revealed that students did not encounter accessibility challenges and expressed preference for shorter podcasts and vodcasts. These multimedia formats alleviated boredom, clarified complex concepts, prevented monotony, enhanced attention and comprehension, stimulated interest, facilitated active learning, and accommodated various learning styles. Podcasts and vodcasts reduced transactional distance and created a sense of community. Contrary to prevailing literature, students did not encounter accessibility challenges, shifting the focus towards shorter, high-quality multimedia content rather than accessibility concerns.

Application of ICU electronic diary platform based on co-design concept in Chinese critically ill patients: a mixed methods study protocol.

Critically ill patients are at a heightened risk for post-traumatic stress disorder (PTSD). While the intensive care unit (ICU) diary has been shown to improve the mental health and quality of life of ICU patients, the handwritten version still has some limitations such as a lack of support for multimedia content and writing by remote family members, as well as being time-consuming and labour-intensive. We hypothesise that constructing an ICU electronic diary platform based on a co-design approach and verifying its applicability could alleviate these limitations, making the ICU diary more convenient for users. This sequential exploratory mixed-methods study will consist of four consecutive phases: understanding the ICU diary research content and implementation, developing an ICU electronic diary platform after conducting qualitative interviews with stakeholders, verifying the applicability of the platform and verifying its effectiveness. Ethics approval was obtained from the Biomedical Research Ethics Committee of the Affiliated Hospital of Zunyi Medical University (approval number: KLL-2023-602). The results of this study will be distributed through peer-reviewed journals. Chinese Clinical Trial Register (ChiCTR2400079903).

Feature-level Fusion vs. Score-level Fusion for Image Retrieval Based on Pre-trained Deep Neural Networks

Today’s complex multimedia content made retrieving images similar to the user’s query from the database a challenging task. The performance of a Content-Based Image Retrieval System (CBIR) system highly depends on the image representation in a form of low-level features and similarity measurement. The traditional visual descriptors that do not provide good prior domain knowledge could lead to poor performance retrieval results. On the other hand, Deep Convolutional Neural Networks (DCNNs) have recently achieved a remarkable success as methods for image classification in various domains. Recently, pre-trained deep convolution neural networks on thousands of classes have the ability to extract very accurate and representative features which, in addition to classification, can also be successfully used in image retrieval systems. ResNet152, GoogLeNet and InceptionV3 are some of the effective and successful examples of pre-trained DCNNs recently applied in a computer vision tasks such as object recognition, clustering, and classification. In this paper, two approaches for a CBIR system, namely early fusion and late fusion, have been presented and compared. The early fusion utilizes concatenation of the features extracted by each possible pair of DCNNs, that is ResNet152-GoogLeNet, ResNet152-InceptionV3, and GoogLeNet-InceptionV3, and the late fusion apply CombSum method with Z-Score standardization to combine the score results provided by each DCNN of the aforementioned pairs. In the experiments on a popular WANG dataset it has been shown that late fusion approach slightly outperforms early fusion approach. The best performance of our experiments in terms of Average Precision (AP) for the top 20 results reaches 96.82%.

Analysis of Influencer Marketing on Social Media Platforms

Influencer marketing is a key factor of organisation advertising and marketing techniques, driven by the sizable use of social media platforms. This research was carried out to examine the determining factors and effect of influencer advertising and marketing on social media structures. We analyzed information accumulated from various social media channels to apprehend the impact of metrics together with likes, remarks, and stocks on logo communique. We additionally utilized social community evaluation to become aware of Key Opinion Leaders (KOLs) and carried out text and multimedia content analysis to delve deeper into the outcomes of content. The consequences display considerable differences in affect factors throughout systems, highlighting the need for tailor-made influencer advertising techniques. This take a look at contributes to the literature on influencer advertising and marketing and offers valuable insights for groups aiming to conduct centered social media advertising.