Video Applications Research Articles

#Wasian Check: Remixing ‘Asian + White’ Multiraciality on TikTok

TikTok is the fastest growing short video application and immensely popular with younger generations to express their thoughts, ideas, and most relevant to this issue, their identities including mixed-race identity. This paper asks: How did young mixed-race people choose to express their identity on TikTok in the #wasian trend and how does the app shape these mixed-race identity expressions? The answer lies in how the emotional affordances of TikTok app itself shape how it is used by creators in mimicking and mimetic ways and how people respond, through video and text. The article argues that the #wasian trends reinforce the racial and genealogical legacy of mixedness, often through showing parents or blood relatives, which is in creative tension with simultaneously remixing and asserting racial multiplicity. The claim to wasianess moves the private sphere (bedroom culture, family and notions of race) into the public and in so doing creates new potentialities for the creation of a global #wasian community on TikTok.

An intelligent optimization algorithm with a deep learning‐enabled block‐based motion estimation model

AbstractThe motion estimation process has gained significant attention in several video applications such as video compression, global motion estimation, and so on. The deep learning (DL) models that perform effectively in computer vision tasks can be employed for motion estimation. Yet, they have high computational complexity and model parameters since motion estimation in the pixel domain is not effective in practical applications. Instead, a block‐based motion estimation process has been developed where the blocks of sequential images are compared. To that end, this paper presents the Anas platyrhynchos optimizer with deep learning‐enabled block‐based motion estimation (APODL‐BBME) model. The proposed model estimates motion using block‐based concepts and DL approaches. To accomplish this, the training and testing frames are separated into non‐overlapping block categories, and the blocks are filtered via the bilateral filtering (BF) approach. In addition, a histogram of gradients (HOG) and densely connected network (DenseNet) model are employed to extract features, which are then fed into the bidirectional long short‐term memory (BiLSTM) model to classify the input features. Finally, the APO algorithm is applied to optimally tune the hyperparameters of the BiLSTM model, which helps to improve the overall motion estimation efficacy, showing the novelty of the work. To demonstrate the enhanced performance of the APODL‐BBME model, a comprehensive analysis is carried out, and when we compare the results, the APODL‐BBME model outperforms recent motion estimation approaches.

Clifford-valued linear canonical transform: Convolution and uncertainty principles

Linear canonical transform is a three-parameter class of linear integral transformation, which has found many applications in optics, filter design, speech, image, video, and signal processing due to its flexibility in representing information within the linear canonical domain. In this article, we extend the linear canonical transform to the class of Clifford-valued signals and introduce a novel transform coined as Clifford-valued linear canonical transform. The primary analysis encompasses the derivation of fundamental properties of the proposed transform such as translation and scaling covariance, inner product relation and inversion formula. Subsequently, we investigate the convolution, continuity, and differentiation theorems for the Clifford-valued linear canonical transform. A non-homogeneous partial differential equation has also been solved in the Clifford framework as an application of the differentiation theorem. Finally, we culminate our investigation by deriving several uncertainty principles for the proposed transform.

Teamwork and Patient Safety in Intensive Care Units: Challenges and Opportunities.

Intensive Care Units (ICUs) are recognized as a susceptible area to potential errors resulting in adverse outcomes. Healthcare professionals are multi-tasking, information-overloaded, and often with an interruptive workflow in ICUs. Such a stressful work environment poses challenges to reach a shared mental model in clinical practice, which leads to ineffective communication and reduces their awareness of potential safety risks. Despite data sources or materials supporting patient safety and team training being available, little research has been conducted to measure teamwork in clinical practice and to detect inefficient communication factors. The advent of telehealth provides an opportunity for remote video watchers to observe the entire process of patient care and related team activities. The potential application of video analyzing algorithms to video recordings can detect safety risks retrospectively. This article presents major teamwork and patient safety challenges in ICUs, and the opportunities of utilizing available data and telehealth including video recordings in future patient safety and teamwork research.

Content-based coding tree unit level rate-quantization model for intra-coding in high efficiency video coding standard using convolutional neural network

In almost all video applications, a video rate control algorithm (RCA) is used by the encoder. The RCA tunes the quantization parameter (QP) to match the encoded bit rate to the available capacity of the communication channel or storage media. Conventional RCAs usually utilize a rate-quantization (R-Q) or a rate-distortion (R-D) model for rate control. A content-based R-Q model for intra coding tree units (CTUs) of the high-efficiency video coding standard is proposed. The model is a convolutional neural network that observes pixels of a CTU and its intraprediction reference pixels and it estimates required bit counts for intracoding the CTU for all QP values simultaneously. The proposed model can be easily used by any video RCA. A given RCA just selects a proper QP for which the estimated bit counts are closer to the allocated bit budget. The evaluation results show a high accuracy for the model. According to simulation results, the mean absolute normalized bit error at CTU level is 19.66% and it decreases to 6.85% at the frame level. Compared with similar networks, the proposed structure has a very low computational complexity.

Improving Student’s Adjective Vocabulary Through Animation Video On Fifth Grade

The purpose of this study was to find out the application of animated videos can improve the adjectives of 5th grade students Mis integrated al-ikhwan tanjung morawa. This type of research is classroom action research (CAR) which is carried out in two cycles. Each cycle consists of three meetings. Furthermore, this research was carried out in four steps, namely planning, action, observation, and reflection. The object of this research is to improve students' adjectives. In collecting data, researchers used tests, observations and documentation. The results of this study indicate that the animation video media has a positive role in increasing the adjectives of the MIS Terpadu Al-Ikhwan Tanjung Morawa students. This can be proven by the average value of students from the initial value, cycle I, cycle II. The average value of the initial score was 57.2, in the first cycle it was 62.4, and in the second cycle it was 81.9.

PENERAPAN VIDEO ANIMASI KARTUN UNTUK MENINGKATKAN HASIL BELAJAR OTK KEUANGAN KELAS XI SMKN 1 SURAKARTA

<p><em>This study aims to improve learning outcomes by using animated cartoon videos in class XI OTKP 3 SMK N 1 Surakarta OTK Finance subjects. This research is a classroom action research. The research was carried out in two cycles, each cycle consisting of planning, implementing actions, observing and collecting data, and reflecting. The subjects of this study were students of class XI OTKP 3 SMKN 1 Surakarta, totaling 34 children. Sources of data used come from teachers and students. Data collection techniques through observation, interviews, tests, and documents. Data validity uses source triangulation techniques, triangulation techniques, comparing data and concluding data. Data analysis used simple quantitative data analysis, qualitative data analysis, and comparative descriptive analysis. The results of the study indicate that learning outcomes can be increased by the application of animated cartoon videos. Based on data collected from pre-action, cycle I, and cycle II have increased, learning outcomes in pre-action as many as 5 students (14.7%) were declared complete, cycle I as many as 18 students (52.9%) were declared complete, and in the second cycle as many as 25 students (73.5%) were declared complete. Learning outcomes data were obtained from the results of the case test as many as 7 questions. The conclusion of this study is that the application of animated cartoon videos can improve learning outcomes of Financial OTK subjects in OTKP students of SMK N 1 Surakarta.</em></p><p> </p>

Utilizing the Inshot Application as A Distance Learning Video

Distance learning at this time results in low delivery of learning materials and learning objectives are not achieved optimally, because teachers only give assignments without learning video learning media, so students do not really understand the learning material, teachers must make learning media at the same time. distance learning by utilizing advanced technology such as using inshot editing applications in learning videos. The goal is for teachers to better know, understand, and increase knowledge about the use of the inshot video editing application as a learning video editing application during the pandemic, because by knowing how to activate learning videos in the inshot application, teachers or it will be easy to make easy, interesting learning videos. , simple, simple. This inshot application has enough features, various features that can be tried for free without paying, this application can be downloaded via the Google Play store on smartphones. And there are several existing features of the inshot application that can be used such as video, split video in two parts or on several clips, adjust video speed, can speed up or slow down video editing, feature to add live audio recording, can control video volume, can rotate videos, Export video files with HD quality, and can crop or remove watermarks on videos. the advantage of the inshot application in video is that it is easy to find information, many interesting features, and can also set the size of the canvas or video size, can share to social media, the inshot application is very suitable for beginners or make simple videos without being complicated and will not interfere when uploading videos.

Using Video as A Learning Media in Class During the Covid-19 Pandemic

Based on the current situation during the COVID-19 pandemic, as well as regulations made by the government to conduct online learning processes, SDN 34 Kinali follows the circulating rules by studying online to help reduce the transmission of COVID-19 that is being faced. So to continue to carry out the learning process, media is needed in conveying material to students, learning media is a tool used to convey material messages to students that stimulate students' minds and attract students' interest in carrying out learning in order to achieve the expected goals in learning. In this study, the purpose of this study was to use an application for editing learning videos at SDN 34 Kinali Pasaman Barat in class V theme 6 sub-theme 1, in making videos in the Kinemaster application, namely by using various features in order to attract students' interest in listening to lessons during the pandemic. Faced at this time. In the current condition, learning videos are very much used so as not to make students lazy in participating in learning that is carried out if only through wa only. Therefore, the kinemaster used in video editing is a good electronic tool and easy to apply.

Emergency Telemedicine Mobile Ultrasounds Using a 5G-Enabled Application: Development and Usability Study.

BackgroundDigitalization affects almost every aspect of modern daily life, including a growing number of health care services along with telemedicine applications. Fifth-generation (5G) mobile communication technology has the potential to meet the requirements for this digitalized future with high bandwidths (10 GB/s), low latency (<1 ms), and high quality of service, enabling wireless real-time data transmission in telemedical emergency health care applications.ObjectiveThe aim of this study is the development and clinical evaluation of a 5G usability test framework enabling preclinical diagnostics with mobile ultrasound using 5G network technology.MethodsA bidirectional audio-video data transmission between the ambulance car and hospital was established, combining both 5G-radio and -core network parts. Besides technical performance evaluations, a medical assessment of transferred ultrasound image quality and transmission latency was examined.ResultsTelemedical and clinical application properties of the ultrasound probe were rated 1 (very good) to 2 (good; on a 6 -point Likert scale rated by 20 survey participants). The 5G field test revealed an average end-to-end round trip latency of 10 milliseconds. The measured average throughput for the ultrasound image traffic was 4 Mbps and for the video stream 12 Mbps. Traffic saturation revealed a lower video quality and a slower video stream. Without core slicing, the throughput for the video application was reduced to 8 Mbps. The deployment of core network slicing facilitated quality and latency recovery.ConclusionsBidirectional data transmission between ambulance car and remote hospital site was successfully established through the 5G network, facilitating sending/receiving data and measurements from both applications (ultrasound unit and video streaming). Core slicing was implemented for a better user experience. Clinical evaluation of the telemedical transmission and applicability of the ultrasound probe was consistently positive.

Effects of Short Video Addiction on the Motivation and Well-Being of Chinese Vocational College Students.

While media use can be beneficial in some ways, excessive use of media has led to growing concerns about its potential negative consequences. With the popularity of Chinese video applications (apps) such as DouYin, TikTok, Kwai, and other short video apps sweeping through schools around the world. Due to the diversity and immersion principle of short videos, their popularity continues to grow, and the phenomenon of students being addicted to short videos also brings many hidden dangers to the learning effect. Among other things, the problem of excessive use of the Internet among Chinese youth has led the government to propose a series of control policies to strengthen the monitoring of harmful habits of youth in the use of online applications. In addition, the problem of youth addiction to short videos has become a major concern for education experts and the general public, thus demonstrating that short video addiction is indeed an ongoing research issue. Therefore, this study aimed to understand the causes of short-form video addiction and its impact on the psychology of learning, and to investigate the relationship between short-form video flow experience, short-form video addiction, intrinsic and extrinsic learning motivation, and learning well-being from the perspectives of flow experience theory and micro ecological systems. The questionnaire was sent via instant messaging software such as QQ and WeChat, and university students from vocational colleges in China were invited to complete the questionnaire. A total of 517 valid data were collected, including 222 (42.9%) were male students and 295 (57.1%) were female students. The collected questionnaires were analyzed for reliability and validity after removing incomplete data, followed by structural equation modeling for model verification. The findings showed that: (1) short video flow experience had a positive effect on short video addiction; (2) short video addiction had a negative effect on intrinsic and extrinsic learning motivation; (3) intrinsic and extrinsic learning motivation had a positive effect on learning well-being; (4) short video flow experience had an indirect negative effect on intrinsic and extrinsic learning motivation; (5) short video flow and short video addiction had indirect negative effects on learning well-being. According to the results, it is clear that addiction to short videos has a negative impact on learners' learning motivation and positive psychology of learning, so parents and teachers should effectively guide students to use short video apps in a self-controlled way.

Adolescent Addiction to Short Video Applications in the Mobile Internet Era.

The adolescent addiction to short video applications is becoming increasingly prominent, which has brought great challenges to the physical and mental health and daily life of the adolescents. This manuscript conducts an empirical study on the contributing factors of the adolescent addiction to short video applications based on the user generated content (UGC). In our study, 96 participants aged 15–25 were surveyed by questionnaire, and then cross-analysis of individual factors and SEM analysis of UGC content factors were carried out. Through the analysis of individual factors of the adolescent addiction from the perspective of gender, age, and family environment, this study reveals that male users are more addicted to the use of applications (APP), and such addiction varies with age, and prolonged family members’ use of short video APP can also exacerbate the adolescent addiction degree. Furthermore, through verification of the theoretical model, it indicates that UGC perception and the degree of boredom in daily life have a significant positive effect on the level of addiction to short video applications, and the degree of boredom in daily life plays a significant mediating role between them. Based on the research on the influences of UGC on the adolescent immersive experience, this study proposes a mechanism of the adolescent addiction to the use of short video applications in the mobile Internet age to provide a better service guarantee for the adolescents.

QoS-Aware Scheduling Algorithm Enabling Video Services in LTE Networks

The Long-Term Evolution (LTE) system was a result of the 3rd-Generation Partnership Project (3GPP) to assure Quality-of-Service (QoS) performance pertaining to non-real-time and real-time services. An effective design with regards to resource allocation scheduling involves core challenges to realising a satisfactory service in an LTE system, particularly with the growing demand for network applications. The continuous rise in terms of the number of network users has resulted in impacts on the performance of networks, which also creates resource allocation issues when performing downlink scheduling in an LTE network. This research paper puts forward a review of optimisation pertaining packet scheduling performance through the LTE downlink system by introducing a new downlink-scheduling algorithm for serving video application through LTE culler networks, and also accounts for QoS needs and channel conditions. A comparison of the recommended algorithms’ performances was made with regards to delay, throughput, PLR, and fairness by utilising the LTE-SIM simulator for video flow. On the basis of the outcomes obtained, the algorithms recommended in this research work considerably enhance the efficacy of video streaming compared against familiar LTE algorithms.

Toward Generalized Psychovisual Preprocessing For Video Encoding

Deep perceptual preprocessing has recently emerged as a new way to enable further bitrate savings across several generations of video encoders without breaking standards or requiring any changes in client devices. In this article, we lay the foundation for a generalized psychovisual preprocessing framework for video encoding and describe one of its promising instantiations that is practically deployable for video-on-demand, live, gaming, and user-generated content (UGC). Results using state-of-the-art advanced video coding (AVC), high efficiency video coding (HEVC), and versatile video coding (VVC) encoders show that average bitrate [Bjontegaard delta-rate (BD-rate)] gains of 11%–17% are obtained over three state-of-the-art reference-based quality metrics [Netflix video multi-method assessment fusion (VMAF), structural similarity index (SSIM), and Apple advanced video quality tool (AVQT)], as well as the recently proposed nonreference International Telecommunication Union-Telecommunication?(ITU-T) P.1204 metric. The proposed framework on CPU is shown to be twice faster than <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\times 264$ </tex-math></inline-formula> medium-preset encoding. On GPU hardware, our approach achieves 714 frames/sec for 1080p video (below 2 ms/frame), thereby enabling its use in very-low-latency live video or game streaming applications.

Offline and Online Social Support and Short-Form Video Addiction Among Chinese Adolescents: The Mediating Role of Emotion Suppression and Relatedness Needs.

Short-form video applications have gained worldwide popularity in recent years. Although short-form video applications encourage communication over the Internet, their popularity encourages adolescents to overindulge in them. This study aimed to explore the effects of offline and online social support (SS) for short-form video addiction (SVA), and the mediating role of emotion regulation and basic psychological needs. A total of 490 junior middle school students from China participated in the study. Structural equation modeling using a bootstrap procedure revealed that (a) offline SS and relatedness needs negatively predicted SVA, (b) pursuit of online SS and emotion suppression positively predicted SVA, (c) emotion suppression and relatedness needs were mediators between offline SS and SVA, and (d) emotion suppression was a mediator between the pursuit of online SS and SVA. These findings provide valuable insight into SVA and will help develop effective strategies for the prevention of SVA.

Development of innovative learning media based on video applications in the introduction to the usage of sewing tools course for fashion students in the state university of malang

The media make it easier for students and lecturers in the student-centered online teaching and learning process, in sewing equipment courses. it is necessary to develop learning media based on video tutorials for operating high speed sewing machines to facilitate online learning. The purpose of this research is to develop three applicable video tutorial products (VTA) namely (overlock sewing machine operation, overdeck sewing machine operation, and buttonhole machine operation). The method used is the ADDIE learning media development model. The results from expert's validation related to media 73.8%, related to material category 96. 8%, and feasible category 89.01%.. The discussion of applicative video tutorials for the operation of overlock sewing machines, overdeck sewing machines, and buttonhole machines begins with the initial display/opening, presentation of sewing machine operation material, ends with assignments/practice. Video displays are made to facilitate and improve students' understanding and motivation in learning. This is because video is one of the efforts to increase understanding and interest in learning for students, which is a technology for capturing, recording, processing, transmitting and rearranging moving images, which are related to vision. and hearing, so that the video is suitable to be used for learning the introduction/use of sewing machines in sewing equipment courses.

Empowering Patients Through Virtual Care Delivery: Qualitative Study With Micropractice Clinic Patients and Health Care Providers.

BackgroundPrior to the wider adoption of digital health technologies during the COVID-19 pandemic, applications of virtual care were largely limited to specialist visits and remote care using telehealth (phone or video) applications. Data sharing approaches using tethered patient portals were mostly built around hospitals and larger care systems. These portals offer opportunities for improved communication, but despite a belief that care has improved, they have so far shown few outcome improvements beyond medication adherence. Less is known about use of virtual care and related tools in the outpatient context and particularly in rural community contexts.ObjectiveThis study aims to reflect on the opportunities and barriers for sustainable virtual care through an example of a digitally enabled rural micropractice, which has provided 10%-15% virtual care since 2016 and 70% virtual care since March 2020.MethodsThree focus groups, 1 with providers (physician and medical office manager) and 2 with a total of 8 patients from a rural micropractice in British Columbia, were conducted in November 2020 and December 2020. Virtual care delivery was explored through the topics of communication approach, mixing virtual and in-person care, the practice team’s journey in developing these approaches, and provider and patient satisfaction with the care model. Interviews were transcribed, checked for accuracy against recordings, and thematically analyzed.ResultsBoth patients and providers reported ease of communication and high satisfaction. Either could initiate communication, and patients found the ability to share health information asynchronously through the portal allowed time to reflect and prepare their thoughts. Patients were highly engaged and reported feeling empowered and true partners in their health care, although they noted limited care coordination with specialists. The mix of virtual and in-person visits was highly regarded by patients and providers, and patients reported feeling safe and cared for 24/7, although both expressed concern about work spilling into the provider’s home life. The physician worried about missed diagnoses with virtual care. With respect to establishing the micropractice, solutions took about 5 years to optimize, with providers noting a learning curve requiring technical support for both themselves and their patients and a willingness to respond to patient feedback to identify the best solutions. Despite a mature virtual practice, patients reported deferred care due to COVID-19.ConclusionsThe micropractice’s hybrid care model encouraged patients to be true partners in their care and resulted in high patient engagement and satisfaction; yet, success may rely on the patient population being willing to engage and being comfortable with technology. Barriers lie in gaps in care coordination and provider fear that signs or symptoms more evident with an in-person exam could be missed. Even in this setting, deferral of care in light of COVID-19 was present, and opportunities to address care gaps should be sought.

Video frame interpolation via down–up scale generative adversarial networks

Frame interpolation finds many applications in video applications, including frame rate up-conversion and video compression. Deep learning-based methods have been proposed for frame interpolation, but a long runtime is typically required to achieve good visual quality. In this paper, we introduce an efficient frame interpolation method based on a modified generative adversarial network. The proposed framework consists of a generator with a pair of down–up scale modules, where the down-scaled-input module attempts to capture the overall structure of the scene while the original-scale-input module aims to restore finer textures. Skip connections and an input processing block are further incorporated into the minimal two-scale generator design to expedite processing without losing image features. The difference between the synthesized frame and the ground truth is measured by a combined loss function, including one adversarial loss and three reconstruction losses. Compared to the state-of-the-art motion compensation and deep-learning based frame interpolation approaches, the proposed framework achieves the most satisfactory trade-off between the synthesis quality and runtime.

Quality Assessment of View Synthesis Based on Visual Saliency and Texture Naturalness

Depth-Image-Based-Rendering (DIBR) is one of the core techniques for generating new views in 3D video applications. However, the distortion characteristics of the DIBR synthetic view are different from the 2D image. It is necessary to study the unique distortion characteristics of DIBR views and design effective and efficient algorithms to evaluate the DIBR-synthesized image and guide DIBR algorithms. In this work, the visual saliency and texture natrualness features are extracted to evaluate the quality of the DIBR views. After extracting the feature, we adopt machine learning method for mapping the extracted feature to the quality score of the DIBR views. Experiments constructed on two synthetic view databases IETR and IRCCyN/IVC, and the results show that our proposed algorithm performs better than the compared synthetic view quality evaluation methods.

Breathing and Relaxation Exercises Help Improving Fear of COVID-19, Anxiety, and Sleep Quality: A Randomized Controlled Trial

Objective: To investigate the effects of breathing and relaxation exercises performed via telerehabilitation on fear, anxiety, sleep quality, and quality of life of individuals without coronavirus disease 2019 (COVID-19) during the ongoing pandemic. Design: A prospective, randomized, controlled single-blind study. Methods: Fifty participants who had not been exposed to the COVID-19 virus earlier were randomly divided into experimental (n = 25) and control groups (n = 25). Both groups received an information session about COVID-19 once at the start of the study via a mobile phone video application. The experimental group also performed a breathing and relaxation exercise program twice daily (morning and evening), 7 days per week, for 4 weeks; one session of the program was conducted under the remote supervision of a physiotherapist as telerehabilitation, and the remaining sessions were performed as a home program. The Fear of COVID-19 Scale (FCV-19S), which was the primary outcome measure, The Hamilton Anxiety Rating Scale (HAMA), Pittsburgh Sleep Quality Index (PSQI), and EQ-5D-3L were administered to both groups. Results: The FCV-19S, HAMA, and PSQI were statistically significantly improved to compare the controls, with a large effect size (ηp2 = 0.135, 0.313, and 0.200, respectively). The EQ-5D-3L index and EQ-5D-3L visual analog scale were not statistically significantly different compared with the controls; however, a small effect size was detected for the differences between the two groups (ηp2 = 0.056 and 0.013, respectively). Conclusion: Breathing and relaxation exercises appear to be an effective and feasible approach to support mental health and sleep quality during the COVID-19 pandemic. Especially in highly contagious diseases such as COVID-19, telerehabilitation approaches may be useful for safely reaching individuals by eliminating human-to-human contact. Clinical Trial Registration number: NCT04910932.