Video Applications Research Articles

Efektivitas Video Berbasis Literasi Sains terhadap Hasil Belajar Mahasiswa

This research aims to determine the effectiveness of scientific literacy-based videos on student learning outcomes. The scientific literacy-based videos have been validated by material experts, media experts, and language experts. The application of scientific literacy-based learning videos is carried out using blended learning, which integrates learning that combines various physical and virtual sources. The research used a pre-experimental, one-group pre-test-post-test design, namely by giving pre-tests and post-tests to students. Data analysis was carried out by determining N-Gain. The research was carried out using the Google Classroom platform. The results of the research show that the N-gain score is 81.6400, so the use of scientific literacy-based learning videos is effective on student learning outcomes. t-tests to students. Data analysis was carried out by determining N-Gain. The results showed that the N-Gain score was 0.8343 on high criteria and 83.43% on effective criteria., so the use of scientific literacy-based learning videos is effective on student learning outcomes.

Semantic-Driven Ghosting-Free Image Fusion Using Dual Gain Video Stream With FPGA

Conventional methods that merge multiple images with different exposure levels often suffer from blur and ghosting due to object movement. Existing ghosting removal algorithms are usually complex and slow, making them unsuitable for real-time video applications. To address this challenge, this study proposes a novel ghosting-free image fusion method using a dual gain video stream setup on an FPGA. IMX662 image sensor is employed, which simultaneously captures both HCG and LCG images with the same exposure time, enabling efficient HDR image synthesis. The proposed method directly addresses the source of the problem, eliminating the need for post-processing steps, thereby preserving algorithmic simplicity. Experimental results reveal that the proposed method not only removes ghosting by 100% but also processes data on an FPGA 98.79% faster than traditional software-based HDR fusion techniques, enabling real-time video stream processing. This dual gain, ghosting-free fusion algorithm demonstrates promising potential for use in high-speed photography and surveillance.

Fusion Model of Quantum Wavelet Transform and Neural Network for Video Coding on the Internet of Things Environment

Solving the video compression problem requires a multi-faceted approach, balancing quality, efficiency, and computational demands. By leveraging advancements in technology and adapting to the evolving needs of video applications, it is possible to develop compression methods that meet the challenges of the present and future digital landscape. To address these objectives, machine learning and AI approaches can be utilized to predict and remove redundancies more effectively, optimizing compression algorithms dynamically based on content. Still, state-of-the art neural network-based video compression models need large and diverse datasets to generalize well across different types of video content. Wavelets can provide both time (spatial) and frequency localization, making them highly effective for video compression. This dual localization allows wavelet transforms to handle both rapid changes in video content and slow-moving scenes efficiently, leading to better compression ratios. Yet, some wavelet coefficients may be more critical for maintaining visual quality than others. Inaccurate quantization can lead to noticeable degradation. For the first time, the suggested model combine Quantum Wavelet Transform (QWT) and Neural Networks (NN) for video compression. This fusion model aims to achieve higher compression ratios, maintain video quality, and reduce computational complexity by utilizing QWT’s efficient data representation and NN’s powerful pattern recognition and predictive capabilities. Quantum bits (qubits) can encode large amounts of information in their quantum states, enabling more efficient data representation. This is especially useful for encoding large video files. Furthermore, quantum entanglement allows for correlated data representation across qubits, which can be exploited to capture intricate details and redundancies in video data more effectively than classical methods. The experimental results reveal that QWT achieves a compression ratio of almost twice that of traditional WT for the same video, maintaining superior visual quality due to more efficient redundancy elimination.

A discussion on the current phenomenon of short video obsession of all ages

This article investigates the underlying reasons for the current phenomenon of short video obsession through a sampling survey and reviewing previous related studies - the social competition among teenagers, the recommendation mechanism of video applications, and the increase in the number of empty nesters. At the same time, the discussion will be extended to the positive and negative impacts of the development of the short video industry on three different age groups, including the academic performance of teenagers, the labor productivity of middle-aged people, and the emotional value of the elderly, further discussing the social environment formed due to the entire short video industry. Finally, the corresponding social impacts were listed and elaborated. In essence, short video has emerged as a practical medium for the rapid dissemination of video information in light of the recent proliferation of the Internet. Individuals across different age groups are driven by distinct motivations to engage with and even immerse themselves in short video applications, owing to their respective life stages.

The Application of Video Transcript on Youtube for Eight Grades Reading Literacy: A Survey Research

This research was written to learn about the application of video transcripts from YouTube videos for students, especially in Reading Literacy. This research uses a Quantitative approach and a questionnaire survey method. The participants of this research were 30 students in 8th-grade Junior High School from Surabaya and Sidoarjo. The aim of this research for to know or compare whether the application of videos with presenting transcript text. The results of this research are that many students are interested in using Transcripts/subtitles when they watch YouTube videos. Therefore, their reading skills are additionally affected by this research. In addition to the video, they watch the text transcription on their device. Usually, they use Digital Apps like Wattpad, Dreame, Webtoon, etc., or use games and social media to support their reading literacy. This research indicated that video transcripts are not only utilized in educational circumstances but in general reading activities outside of the classroom as well.

PaCs: Playing Time-Aware Chunk Selection in Short Video Preloading

Short video applications are popular nowadays. Typically, a short video may be played for a few seconds or swiped away by users at any time. Due to this uncertain user behavior, video chunks should be preloaded to ensure a smooth viewing process for users. In other words, the short video preloading scheme is crucial to the quality of experience (QoE) of users and revenue. Specifically, the short video preloading scheme should determine which video chunk to download, when to download it, and at what bitrate. Existing schemes either fail to consider all these factors together or find it hard to make the best decision. In this work, we argue that the selection of downloaded video chunks is the foremost task due to the uncertain user behaviors and the corresponding huge number of possible playing sequences of video chunks. As a step further, we propose the playing time-aware chunk selection (PaCs) scheme, which downloads the video chunk with the smallest expected playing time first. After the selection of the video chunk, the bitrate is selected according to the classic MPC algorithm and then whether the downloading process is paused or executed is discussed. In total, PaCs can improve the score consisting of the QoE of downloaded video chunks and the utilized network bandwidth under different conditions. Simulations confirm that PaCs achieves a higher score than the existing scheme Dashlet proposed in NSDI 2024.

Application of Video Based Learning Method to Increase Student Engagement in the Digital Age

The rapid development of digital technology has revolutionized the educational landscape, which demands more innovative and engaging teaching methods. One such method is Video-Based Learning (VBL), which utilizes multimedia resources, such as videos, to enhance students' learning experience. This article discusses the application of VBL as a strategy to enhance student engagement in the classroom in the context of the digital age. The research examines the effectiveness of VBL in encouraging active participation, enhancing understanding and strengthening students' motivation to learn. By integrating video content in the learning process, educators can provide a dynamic and interactive learning environment that suits various learning styles. In addition, VBL facilitates access to resources beyond traditional teaching, allowing students to interact with learning materials according to their pace and preferences. This research demonstrates the positive impact of VBL on student engagement, especially in subjects that benefit from visual and auditory stimulation, and discusses challenges and solutions in effective implementation. This article aims to provide insights and practical guidelines for educators in integrating Video-Based Learning in their teaching practices, so that students are better equipped to thrive in the digital age.

Longitudinal Associations Between TikTok Use, Self-Concept Clarity, and Anxiety Among Chinese Emerging Adults: Exploring Differential Impacts of Active and Passive TikTok Use

Short-form video applications, such as TikTok, have gained significant popularity among emerging adults. We conducted a longitudinal study to gather data at three time points from two universities in South China. A total of 590 university students ( M age = 19.83; SD age = 1.24) completed the questionnaires measuring active and passive TikTok use behaviors at time 1 (T1, April 2022), self-concept clarity at time 2 (T2, October 2022), and anxiety both at Time 1 (T1, April 2022) and at Time 3 (T3, April 2023). The results showed that T1 active TikTok use had a negative correlation with T3 anxiety ( r = −0.23, p < .001), while T1 passive TikTok use had a positive correlation with T3 anxiety ( r = 0.30, p < .001). Both T1 active TikTok use (95% CI [0.03, 0.09]) and T1 passive TikTok use (95% CI [0.07, 0.16]) can predict T3 anxiety indirectly by reducing T2 self-concept clarity. Moreover, even after considering T2 self-concept clarity, the direct impact of T1 active TikTok use on T3 anxiety remained significant (95% CI [−0.24, −0.09]), but the direct effect of T1 passive TikTok use on T3 anxiety was not significant (95% CI [−0.04, 0.12]).

Fuzzy proportional-integral-derivative rate controller for variable bitrate applications of versatile video coding standard

Fuzzy proportional-integral-derivative rate controller for variable bitrate applications of versatile video coding standard

Short-Form Video Applications Usage and Functionally Dependent Adults' Depressive Symptoms: A Cross-Sectional Study Based on a National Survey.

This study constructed a theoretical model based on the social compensation theory and used it to investigate the effects of short-form video applications usage on depressive symptoms among functionally dependent adults. An empirical analysis was conducted based on a national sample of 8752 adults aged 45+ from China Family Panel Studies (CFPS) wave 2020. This study examined the effects of short-form video applications usage on depressive symptoms in functionally dependent adults by constructing linear regression models. Further, the mediating effect of interpersonal relationship, and the moderating effect of video games were then sequentially analyzed with the help of macro PROCESS4.0 tool. Results showed that: (1) short-form video applications usage significantly reduced the level of depressive symptoms among functionally dependent adults; (2) interpersonal relationship exerted a mediating effect of 10.36% in the process of short-form video applications usage reducing the level of depressive symptoms among functionally dependent adults; (3) video games attenuated the healing effect of short-form video applications usage on the level of depressive symptoms in functionally dependent adults, but not significantly in the functionally dependent adults aged 60+. New electronic media, represented by short-form video applications, have the potential to intervene in the mental health of functionally dependent adults. Social policymakers should consider adopting relevant e-healing measures to enhance the well-being of vulnerable groups.

Automatic exposure strategy network for robust visual odometry in environments with high dynamic range

The success of visual-based localization requires the image features to be sufficiently captured in well-exposed images and reliably tracked among image sequences. In this paper, a learning-based exposure strategy algorithm is developed to improve the performance of visual odometry or simultaneous localization and mapping in scenes with sudden illumination changes and high dynamic range (HDR). The exposure value is predicted by optimizing a novel image information metric, which is calculated based on a multi-scale image histogram. Experimental observations show that the proposed metric is highly related to the localization performance, and achieves better localization accuracy when compared to other state-of-the-art metrics. Using this novel metric, the exposure control network is designed to predict the exposure value for the next image given a sequence of recently captured images as inputs. For different application scenarios, alternative network frameworks are proposed with the options to include an optimization module providing improved exposure values for feedback learning, but with additional computation complexity. The approach is light-weight for real-time video applications and the images captured using the predicted exposure values are well-exposed with better detected and matched features in a variety of challenging HDR scenes. Code will be available in https://github.com/leejieyu13/HDR-AE.

Game-theory-based complexity allocation for 360-degree video coding

360-degree video applications with immersive experiences have been well spread in our daily life. However, 360-degree video with high resolution (e.g., 8192×4096,6144× 3072, and 3840 × 1920) leads to high coding computational complexity. To further optimize the complexity allocation and obtain the optimal coding performance, this paper proposes a game-theory-based complexity allocation algorithm for 360-degree video coding. The proposed method first constructs the latitude-level complexity allocation model by introducing game theory. Second, the optimal Lagrange coefficient λ∗ value is obtained by the Newton method, and then, the complexity of the latitude can be further obtained. Finally, the overall complexity allocation algorithm is also designed. Experimental results indicate our method obtains Time Saving (TS) with 18.44%∼67.08% and BDBR performance with 0.10%∼3.11%. The proposed method also achieves the optimal Coding Gain (CG) values for the most global target complexity.

A Virtual View Acquisition Technique for Complex Scenes of Monocular Images Based on Layered Depth Images

With the rapid development of stereoscopic display technology, how to generate high-quality virtual view images has become the key in the applications of 3D video, 3D TV and virtual reality. The traditional virtual view rendering technology maps the reference view into the virtual view by means of 3D transformation, but when the background area is occluded by the foreground object, the content of the occluded area cannot be inferred. To solve this problem, we propose a virtual view acquisition technique for complex scenes of monocular images based on a layered depth image (LDI). Firstly, the depth discontinuities of the edge of the occluded area are reasonably grouped by using the multilayer representation of the LDI, and the depth edge of the occluded area is inpainted by the edge inpainting network. Then, the generative adversarial network (GAN) is used to fill the information of color and depth in the occluded area, and the inpainting virtual view is generated. Finally, GAN is used to optimize the color and depth of the virtual view, and the high-quality virtual view is generated. The effectiveness of the proposed method is proved by experiments, and it is also applicable to complex scenes.

How stress influences short video addiction in China: an extended compensatory internet use model.

The rise of short video applications has become a defining feature of modern digital media consumption, drawing increasing attention from researchers due to issues related to short video addiction. While earlier studies have examined the perceived stress as a cause of short video addiction, there is limited understanding of the potential mechanisms underlying the relationship between these two variables. Building on compensatory Internet use (CIU) theory, this study introduces an extended model (E-CIU) to explore how stress, compensatory motivations (i.e., social interaction and relaxing entertainment), and affective responses (i.e., immersion and attitude) relate to short video addiction. This study also examines differences between the age groups. Data from 319 Chinese short video users were tested applying partial least squares structural equation modeling (PLS-SEM) and PLS-SEM multigroup analysis. Findings indicate that stress, immersion, and attitude each contribute positively to short video addiction. Stress is linked to both social interaction and relaxing entertainment. While both factors positively affect attitude toward short videos, only relaxing entertainment enhances immersion. Results confirmed the perceived stress indirectly influences short video addiction through a serial mediating pathway comprising motivations and affective responses. Moreover, the study shows that perceived stress influences social interaction, relaxing entertainment influences attitude and immersion, and social interaction influences immersion across all age groups. The study further identified variations in how different groups experience the relationship between stress and addiction, stress and relaxation, attitude and addiction, and immersion and addiction. Consequently, this study enriches the understanding of the E-CIU as a new theoretical model of short video addiction. These insights offer practical recommendations for short video applications to address user engagement and addiction more effectively.

Consumer impulse buying in Hungary: A CB-SEM analysis of Hungarian consumer behaviour towards mobile short video applications based on a Chinese reference model

Mobile Short Video Applications are becoming increasingly popular worldwide. The appropriate content can shape, improve or change consumers' purchasing decisions. This paper examines the attitudinal differences in impulse buying related to the use and acceptance of MSAs by adapting a model already validated in China to Hungarian users. The analysis was conducted using Covariance-Based Structural Equation Modelling (CB-SEM). A structured questionnaire survey of 283 respondents in Hungary shows that the Chinese model cannot fully be applied to Hungary. A major difference between the results of the two models is that in the Hungarian model, perceived expertise shows a positive relationship with flow experience. This indicates that video makers - in the case of Hungarian videos - should produce content including introductory information and the operation of the product. The results suggest that in the case of MSA use in Hungary, perceived expertise affects impulse buying indirectly, but flow experience directly. Flow experience is only influenced by perceived expertise (β = 0.31, ρ < 0.05), with an explained variance of 10%. Flow experience (β = 0.46, ρ < 0.05) with its direct effect on impulse buying behaviour accounts for 21% of the variance. Hungarian and Chinese MSA users have different preferences in terms of content, thus the results provide important information for both international short video creators and companies entering the international market.

Effect of virtual reality video application on fistula puncture-associated pain in patients undergoing hemodialysis: Assessor-blinded randomized trial.

To elucidate the effect of virtual reality video application on fistula puncture-associated pain in patients undergoing hemodialysis. Attention controlled and assessor-blinded randomized trial. Attention controlled and assessor-blinded randomized trial was conducted 28 patients at the hemodialysis center of City Hospital. The patients in the intervention group (n = 14) participated in 12 hemodialysis sessions with virtual reality video application under the researcher's supervision. The patients in the control group (n = 14) received a 6-min training session on diet compliance. The Sociodemographic Form and Visual Analog Scale were used to collect data in person at various time points: baseline (t0), during the 1st to 12th hemodialysis sessions (t1-t12), and 1 week after implementation (t13). Virtual reality video application helped in effectively decreasing pain over time, as revealed by significant differences in the measurements at t1-t12 and t13 (p < 0.05). Time-based variations in within-group differences revealed that the median fistula puncture-associated pain values were significantly higher at baseline and t13 measurements in the intervention group (p < 0.05). In contrast, no significant differences were observed in the median fistula puncture-associated pain values in the control group (p < 0.05). In patients undergoing hemodialysis, the application of virtual reality helps decrease fistula puncture-associated pain values. Advances in technology, particularly virtual reality, may play a vital role in shaping the future of healthcare.

Effects of short video addiction on college students' physical activity: the chain mediating role of self-efficacy and procrastination.

Excessive use of short video applications can adversely affect the physical and mental health of college students. At present, regarding the effect of short video addiction on physical exercise, few scholars have studied the mechanism of action. This study aims to investigate the mechanism by which short video addiction impacts college students' physical exercise. Therefore, we investigated the correlation between short video addiction and physical activity, and examined the influence of self-efficacy and procrastination on this relationship. In this research, 304 college students were selected as survey subjects. The questionnaires included Short Video Addiction Scale, Physical Activity Rating Scale, General Self-Efficacy Scale, and Short Version General Procrastination Scale. The data underwent correlation analysis using SPSS and mediation effect analysis using the PROCESS macro program. (1) 61.51% (187) of college students' physical activity was low exercise. (2) Physical activity was significantly negatively impacted by short video addiction. (3) Self-efficacy played an independent mediating role in the association between short video addiction and physical activity. (4) The association between short video addiction and physical activity was independently mediated by procrastination. (5) Self-efficacy and procrastination function as chain mediators in the association between short video addiction and physical activity. Our research identifies the role that self-efficacy and procrastination play in the connection between short video addiction and physical activity. Decreasing the utilization of short video applications and enhancing self-efficacy can reduce procrastination and improve physical activity for college student groups.

Douyin—— the leading application in short video in the next decade

In recent years, along with the comprehensive innovation of communication technology, new media has also achieved rapid development and gradually penetrated into various fields. According to the 48th Statistical Report on the Development of the Internet in China released by the China Internet Network Information Center, as of June 2021, the number of Internet users in China has reached 1.011 billion, of which 888 million are short video users, accounting for 87.8% of the total Internet users. According to the survey results of the products most commonly used by short video users from 2020 to 2021, Douyin ranked first with 45.2%. As one of the emerging social media, Douyin short video APP is different from the previous simple graphic social, but the combination of music, special effects and video, so as to closely connect users of different ages, industries and identities. Based on this, this paper will discuss the possibility of Douyin platform to achieve fine operation and further expand market share by optimizing user generated content (UGC) model and analyzing the personality and commonality of audience psychology.

Association between parental phubbing and short-form video addiction: A moderated mediation analysis among Chinese adolescents

BackgroundShort-form video applications have spread rapidly and gained popularity among adolescents for their interactivity, sociality, and personalization. However, excessive and uncontrolled use has also caused some adolescents to develop short-form video addiction (SFVA). Although parental phubbing has been shown to be a risk factor for SFVA in adolescents, its intermediate mechanisms, particularly the emotional mediation mechanisms, remain unclear. Therefore, this study aims to explore the relationships among parental phubbing, SFVA, symptoms of depression and anxiety, and neuroticism in adolescents. MethodsAdolescents aged 13–19 (N = 5785) were recruited from Shandong Province, China, as participants in 2023. Participants were asked to complete five self-report questionnaires, including the Parental Phubbing Behavior Questionnaire (PPBQ), Short-Form Video Addiction (SFVA) Scale, The Center for Epidemiological Studies Depression Scale (CESD20), Generalized Anxiety Disorder 7-item (GAD-7) Scale, and Chinese Big Five Personality Inventory (Brief Version) (CBF-PI-B). ResultsThe results indicate that the influence of parental phubbing on short-form video addiction among adolescents is mediated by symptoms of depression and anxiety. Additionally, neuroticism moderates the association between parental phubbing and symptoms of depression and anxiety. LimitationsCross-sectional design limits causal inferences. Reliance on self-report scales. ConclusionsThese findings contribute to a better understanding of the systemic impact mechanisms of negative family interactions on SFVA. Moreover, prevention and intervention strategies targeting high neuroticism and symptoms of depression and anxiety may help prevent the developmental pathway from parental phubbing to SFVA.

ACroSS: AI-driven cross-layer adaptive streaming for short video applications

As short video applications gain popularity, researchers are exploring ways to enhance Quality of Experience (QoE) for short videos while maximizing network bandwidth efficiency. Despite the growing interest, existing Adaptive Bitrate (ABR) algorithms primarily concentrate on content prefetching strategies and often overlook the dynamic interaction between network congestion control and ABR. This interaction is especially critical for short video streaming, where network conditions can fluctuate rapidly, and user expectations for seamless playback are high. To address these challenges, we propose aCroSS, an AI-driven framework for adaptive short video streaming that jointly optimizes both the application and transport layers to enhance QoE and bandwidth utilization. The aCroSS algorithm leverages advanced machine learning techniques to adapt in real time to fluctuating network conditions and dynamic user behaviors, delivering a more robust and responsive streaming experience. Our simulation results demonstrate that aCroSS consistently outperforms existing baseline algorithms, achieving more than a 10% improvement in utility scores across various network trace datasets. This highlights the effectiveness of aCroSS in delivering superior performance in diverse streaming environments.