Similar Video Research Articles

AI in Video Recommendation System

Short videos are very popular all over the world. Video recommendation system is an essential part in it. It can help people to watch the video that they are interested in. This paper is written for study the specific principle of the video recommendation system. The result was getting through relative literatures and actual test. Short video recommendation systems typically use collaborative filtering and deep learning techniques to achieve this. Collaborative filtering comes in two types: user-based and content-based. User-based collaborative filtering recommends videos to new users based on the viewing behavior of similar users. Content-based collaborative filtering uses video features and similarity to recommend similar videos. Finally, this paper shows how the video web set can learn what is the user’s interest.

Making Sense of Responsibility: A Semio-Ethic Perspective on TikTok’s Algorithmic Pluralism

Utilizing the data collected from 40 in-depth interviews, this study explores: How do users perceive social media platforms’ responsibility in designing algorithms? What do users perceive as diverse or similar in the content generated by algorithmic recommendation systems? The analysis discusses and evaluates the tension between (a) how the platform’s algorithm feeds users similar videos that they highly appreciate and, inversely, (b) how the recommendation of similar videos might limit the diversity of content to which the user is exposed. The analysis adopts a semio-ethic framework to understand why algorithmic platforms like TikTok are perceived to be so efficient in promoting an apparent perception of inclusivity while deliberately erasing alterity and promoting universal sameness. Although videos recommended by TikTok might appear to satisfy computational criteria of diversity, the outcome masks the absence of algorithmic pluralism. The algorithm generates socially desirable videos to allow users to feel comfortable in their in-group. In other words, recommended videos perpetuate a digital form of conformism in a conscious attempt to create the illusion of a more plural community. Advancing the study of algorithmic pluralism is therefore crucial to evaluate the extent to which plurality is understood by users, and what assumptions and ethics underpin the cultures that foster algorithmic recommendation design.

Promote identification or prevent expansion? The effect of uploader-viewer similarity on viewer inspiration in the context of short video community.

Short video communities have proliferated recently, opening up a new channel for the promotion of online businesses. The main challenge in marketing with short videos is how to inspire consumers. This study employs viewer social identification and self-expansion as its entrance point to to explain how uploader-viewer similarity affects viewers' short video inspiration. We use empirical investigation method based on the data of 310 short video viewers to test our conceptual model. We found that there is a double-edged relationship between uploader-viewer similarity and short video inspiration. Particularly, uploader-viewer similarity enhances perceived social identification while reducing perceived self-expansion. The association between Uploader-viewer similarity and short video inspiration is moderated by viewers' cognitive demands. These results provide a new perspective for enterprises to manage the relationship between viewers and media.

Personal protective equipment use among dental healthcare personnel during the coronavirus disease 2019 (COVID-19) pandemic and the impact of an educational video in clinical practice.

Dental healthcare personnel (DHCP) are at high risk of exposure to coronavirus disease 2019 (COVID-19). We sought to identify how DHCP changed their use of personal protective equipment (PPE) as a result of the COVID-19 pandemic, and to pilot an educational video designed to improve knowledge of proper PPE use. The study comprised 2 sets of semistructured qualitative interviews. The study was conducted in 8 dental clinics in a Midwestern metropolitan area. In total, 70 DHCP participated in the first set of interviews; 63 DHCP participated in the second set of interviews. In September-November 2020 and March-October 2021, we conducted 2 sets of semistructured interviews: (1) PPE use in the dental community during COVID-19, and (2) feedback on the utility of an educational donning and doffing video. Overall, 86% of DHCP reported having prior training. DHCP increased the use of PPE during COVID-19, specifically N95 respirators and face shields. DHCP reported real-world challenges to applying infection control methods, often resulting in PPE modification and reuse. DHCP reported double masking and sterilization methods to extend N95 respirator use. Additional challenges to PPE included shortages, comfort or discomfort, and compatibility with specialty dental equipment. DHCP found the educational video helpful and relevant to clinical practice. Fewer than half of DHCP reported exposure to a similar video. DHCP experienced significant challenges related to PPE access and routine use in dental clinics during the COVID-19 pandemic. An educational video improved awareness and uptake of appropriate PPE use among DHCP.

Comparative Analysis of the Consumption Phenomena of Hong Kong Postgraduates via Tiktok and Bilibili Based on In-depth Interviews and Questionnaires

The attraction of Bilibili to young audiences is increasing year by year. The explosion of Tiktok has made a certain impact on the popularity of Bilibili. Therefore, it is particularly vital to explore the deep consumption causes behind young people. At present, there is relatively little research on the comparison between Bilibili and Tiktok video platforms, including the consumption psychology of the audience. This kind of research is relatively novel and mainly employed and disseminated in the industry. Therefore, academic research is still rather rare. Meanwhile, there is a lack of in-depth and systematic research results. This study tries to investigate Hong Kong graduate groups from eight prestigious public universities through in-depth interviews and questionnaire surveys, using SPSS software for data analysis. By collecting the comments and feedback of postgraduate students on Bilibili and Tiktok, the consumption status of young audiences and the underlying consumption reasons can be understood. The commercial value will be provided to those similar video broadcast platforms’ business modes. The research suggests that young audiences with a certain educational background have not been significantly affected by using Tiktok, although the popularity of Tiktok in recent years is reflected in the increasing data. Comparatively, Bilibili is relatively attractive to this group. This group will not blindly engage in impulsive consumption on the platform. The underlying consumption reasons can be summarized as follows: the upgrading of the consumption concept, the demand for functional products, better daily consumption platform alternatives, and the fondness for anchors.

Utilizing 3-Dimensional Cardiac Models With Point-of-Care Ultrasound Video Tutorials to Improve Medical Student Education: A Double-Blinded Randomized Control Study.

Introduction Ultrasound is a rapidly expanding imaging modality that many medical schools are incorporating into a structured curriculum. Learning both anatomy and ultrasound imaging simultaneously is intuitively challenging. This double-blinded, randomized control study examined the effect of utilizing three-dimensional (3d) cardiac models within an ultrasound video tutorial in order to achieve improved cardiac ultrasound anatomy education. Methods Thirty-nine (39) first- and second-year medical students at a single medical school voluntarily participated. The control group watched a video tutorial on cardiac ultrasound anatomy while the experimental group watched a similar video tutorial that also included a 3d cardiac model. The effect was measured with a multiple-choice test that included a sub-analysis of ultrasound principles. The test was unique in that no text or context clues were provided on the reference images, further challenging anatomic identification. Results The findings of the study included a p-valueof 0.73 for the ultrasound principles section and a p-value of 0.77 for the cardiac anatomy. There was no statistical difference in the primary outcome or in the subgroup analysis. Post-hoc analysis demonstrated the study was underpowered. Conclusions This study is the first of its kind to utilize an innovative testing method that holds promise for future research in regards to utilizing 3d models with ultrasound education. The study was underpowered, therefore no definitive conclusions about the utility of 3d cardiac models in the educational process can be ascertained.

Impact of Video Education to Train Trauma Staff

Background:Management of trauma patients is challenging and requires a coordinated team effort inside a crowded trauma bay. Errors can result in disastrous consequences. Trauma is the leading cause of death in the United States of people younger than the age of 45. Maintaining a cohesive team dynamic is paramount, but academic medical centers must deal with the constancy of rotating staff and learners that may be unfamiliar with resuscitation workflows. This project aims to improve the trauma resuscitation process by identifying the gaps in knowledge and process through auditing of the highest-level trauma activations.
 Methods:This is a pre- and post-intervention prospective cohort study of adherences to a standardized trauma resuscitation process through the use of an educational video at a busy level 1 academic trauma center. Process improvement resulting from the educational video will be assessed quantitatively through in-person and video review audits using a pre-defined checklist. This checklist scores the crucial elements highlighted in the educational video that must be addressed in each trauma resuscitation. The goal of this project is to illustrate improvement of the trauma resuscitation process through the comparison of trauma resuscitations audited before and after implementation of the training video.
 Results:The most commonly observed deficits have been related to the donning of correct personal protective equipment (PPE) and communication. The most common PPE left out was eye protection and hair covering. Shortcomings in communication include failure to practice 1:1 communication and the performance of adequate pre-briefs.
 Potential Impact:This study will establish a feasible method of improving the trauma resuscitation process at IU Health Methodist Hospital. Potential next steps of this study’s conclusions include improving the trauma resuscitation process at other Indianapolis trauma 1 centers outside of Methodist Hospital, and the implementation of similar video education training for additional team-based procedures.

Analysis of network function sharing in Content Delivery Network‐as‐a‐service slicing scenarios

AbstractVideo content consumption is currently dominating the mix of traffic observed in Internet service provider (ISP) networks. The distribution of that content is usually performed by means of content delivery network (CDN) caches storing and delivering multimedia. The advent of virtualization is calling attention to the CDN providers as a use case for virtualizing the cache function. In parallel, there is a trend for sharing network infrastructures as a way of reducing deployment costs by ISPs. Then, an interesting scenario emerges when considering the possibility of sharing virtualized cache functions among ISPs which are sharing a common physical infrastructure, mostly considering that those ISPs offer similar video content catalogs to end users. Furthermore, when deciding to share the caches among ISPs, it is interesting to understand the impacts due to limiting the storage capacity at the edge sites. This paper investigates through simulations the potential efficiencies that can be achieved when sharing a virtual cache function if compared with the classical approach of independent virtual caches operated per ISP, as well as the implications of limiting the storage capacity of the caches at the edge.

The Magical Art of Technical Presentations [Perspectives

At the time of publication, all of the links in this article were operational. However, since we do not host the videos, we have no control over whether or not they will continue to be active. In many cases, similar or related videos can be found by typing the performer’s name in an appropriate search engine. For convenience, all of the referenced links can also be accessed at <uri xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">www.fourhandedillusions.com/matp</uri> . On occasion, new and related links might also be posted on that site.

Simultaneous Video Retrieval and Alignment

With the growth of the video streaming industry, video retrieval and video alignment are facing high levels of demand. Several studies have demonstrated the feasibility of these methods for various problems related to video retrieval and alignment independently, but test in a unified framework has never been done. However, in real-world applications, it is also concurrently necessary not only to find which video pairs are similar (video retrieval) but also to align the positions of the pair that are related (video alignment). In this paper, we present a new task that simultaneously retrieves and aligns videos. As a solution to this task, a simultaneous retrieval and alignment framework abbreviated as SRA is proposed, which is a two-stage approach consisting of a foreground proposal stage and a downstream stage to efficiently process untrimmed videos. Furthermore, two criteria are suggested to support the new task: a metric mAP@J assessing how highly the related videos are ranked and how well relevant positions are assigned in that video, and a dataset FIVR+A that includes video-level relationships and hierarchical segment-level annotations. Finally, we conduct multi-pronged analyses to assess how our approach handles the new task in various experiments.

A Study on the Success of Short Videos Themed on Beijing Cuisines and Its Influence on the City’s Image

With the boom of the short video industry in recent years, cities with tremendous internet influences have witnessed rapid growth attributable to the rise of short video platforms where cuisinethemed short videos have become a new channel for the communication of a city’s image. On one of the platforms, TikTok, there exists a huge gap in terms of communication performance among cuisine-themed short videos of different kinds. Taking content analysis as the tool, this paper is engaged with the quantitative analysis of the content characteristics, food types, city image, video length and language characteristics of the short videos themed on Beijing cuisines that go viral on the Internet with the coded information extracted from the top 30 related short videos with most likes published on TikTok, so as to investigate their commonalities and shared features. An in-depth analysis is provided as the result with specific cases taken into account to propose for the production and communication of similar videos and to provide certain references for the construction and communication of the image of corresponding cities.

Research on the Content of Short Videos of Science Popularization

Nowadays, the Internet is highly developed and self-media has emerged. As one of the new communication channels, self-media is favored by internet users and enterprises because of its rapid transmission of information and high interactivity. With the continuous improvement of people's living standard, the demand for spiritual and cultural aspects is also increasing, and the traditional TV media can no longer meet the growing spiritual and cultural needs of the public nowadays. Therefore, the new era of television media has to seek changes. Here comes the most popular form of content, short video. Among them, beeping technology area up master "Hello teacher, my name is He" with super high quality video content, eye-catching circle hot research for a large number of young audiences favored. The author believes that the study of the content of this self-media can help provide some insights for the development of science popularization self-media and similar science popularization short video uploaders. In terms of content, the author adopted the content analysis method to study the 43 videos of "Hello teacher, my name is He" in the past five years. The author found that: "Teacher, my name is He" videos are mainly divided into several aspects, such as in-depth experience evaluation, hot science videos and fan feedback videos; the update frequency and release volume of He showed a relatively stable dissemination trend, and the videos are mostly 5-8 minutes short videos.

Pengaturan Pertanggungjawaban Pelaku Penyalahgunaan Deepfakes Dalam Teknologi Kecerdasan Buatan Pada Konten Pornografi Berdasarkan Hukum Positif Indonesia

Deepfakes as a derivative subset of the use of artificial intelligence technology have the ability to manipulate images or videos that overlay faces on other people's bodies with the intention of creating new videos with false representations. Initially this deepfakes ability was used in filmmaking and has now been applied to the features of mobile applications, but in reality there is an abuse of its ability to make a video with pornographic content. In Indonesia, there have also been several cases of similar pornographic videos featuring Indonesian artists in their videos and have been spread on the internet. Indonesia itself does not have special regulations regarding artificial intelligence technology, only explicitly stated in Law Number 19 of 2016 concerning Amendments to Law Number 11 of 2008 concerning Information and Electronic Transactions (UU ITE). This study was structured using normative juridical methods, using library data collection procedures, and document study data collection techniques. The study was conducted to discuss the legal basis for violations that occur when someone (the perpetrator) abuses the ability of deepfakes to make a video with pornographic content according to Article 29 jo. Article 4 paragraph (1) and Article 35 jo. Article 9 of Law Number 44 of 2008 concerning Pornography is an act that is prohibited and accompanied by criminal sanctions as a form of criminal responsibility for the perpetrators.

Efficient Content Based Video Retrieval System by Applying AlexNet on Key Frames

The video retrieval system refers to the task of retrieving the most relevant video collection, given a user query. By applying some feature extraction models the contents of the video can be extracted. With the exponential increase in video data in online and offline databases as well as a huge implementation of multiple applications in health, military, social media, and art, the Content-Based Video Retrieval (CBVR) system has emerged. The CBVR system takes the inner contents of the video frame and analyses features of each frame, through which similar videos are retrieved from the database. However, searching and retrieving the same clips from huge video collection is a hard job because of the presence of complex properties of visual data. Video clips have many frames and every frame has multiple properties that have many visual properties like color, shape, and texture. In this research, an efficient content-based video retrieval system using the AlexNet model of Convolutional Neural Network (CNN) on the keyframes system has been proposed. Firstly, select the keyframes from the video. Secondly, the color histogram is then calculated. Then the features of the color histogram are compared and analyzed for CBVR. The proposed system is based on the AlexNet model of CNN and color histogram, and extracted features from the frames are together to store in the feature vector. From MATLAB simulation results, the proposed method has been evaluated on benchmark dataset UCF101 which has 13320 videos from 101 action categories. The experiments of our system give a better performance as compared to the other state-of-the-art techniques. In contrast to the existing work, the proposed video retrieval system has shown a dramatic and outstanding performance by using accuracy and loss as performance evaluation parameters.

What are the ethical considerations of using video social media platforms such as TikTok in your dental practice?

What are the ethical considerations of using video social media platforms such as TikTok in your dental practice?

A Heuristic Video Recommendation Algorithm based on Similarity Computation for Multiple Features Analysis

Objective:: The short video applications have achieved great success in recent years. The number of videos being shot and uploaded to these platforms has increased greatly. In this way, mining and recommending videos for users based on their interests have become a very difficult problem in these video distribution platforms. Under this case, it becomes particularly important to design efficient video recommendation algorithms for these platforms. In order to solve the problem faced by high sparsity and large scale data sets in the field of media big data mining and recommendation, a heuristic video recommendation algorithm for multi-dimensional feature analysis and filtering is proposed. Methods:: Firstly, the video features are extracted from multiple dimensions such as user behavior and video tags. Then, the similarity analysis is carried out, and the video similarity degree is calculated by weighting, so as to obtain the similar video candidate set, and filter the similar video candidate set. After that, the videos with the highest scores are recommended to users by sorting. Finally, the video recommendation algorithm proposed in this paper is implemented by using the C language. Results:: Compared with the benchmark, the proposed video recommendation algorithm has improved the accuracy by 6.1%-136.4%, the recall rate by 19.3%-30.9%, the coverage rate by 55.6%-59.5%, the running time by 42.7%-60.4%, and the cache hit ratio by 10.9%-47.4%. Conclusion:: The proposed algorithm can effectively and greatly improve the accuracy, recall rate, coverage rate, running time and cache hit ratio.

Constructing online destination brand experience and bilateral behavioral intentions: a sensory conduction perspective

ABSTRACT The emergence of short-form videos brings the sensory experience of the destination from offline to online and connects with the online destination brand experience (ODBE). Within the data crawled from short-form video content about Moshi Park, the study explored users’ destination sensory stimulation. Furthermore, we propose a cognitive–affective-conative model to investigate the relationship between sensory experience, ODBE and behavioral intentions. The results illustrate that visual stimuli dominate in the five senses, and hearing, touch, smell, and taste play an auxiliary role in influencing specific brand experience dimensions. All brand experience dimensions have a positive impact on users’ offline visit intention. However, affective and behavioral brand experience fails to motivate users to continue watching similar videos online for potential aesthetic fatigue and substitution effects. This study fills the research gap by examining the experiences and subsequent behaviors elicited by users watching short-form videos of tourist destinations. The model and discovery have made valuable contributions to refine sensory theory and brand experience, especially for virtual environments with advanced technology.

Joint Transcoding- and Recommending-Based Video Caching at Network Edges

Edge caching can significantly improve the quality of wireless video services by deploying cache servers at network edges. Recently, video conversion and recommendation have been introduced to improve the caching performance at the edges. Specifically, they work to produce lower quality versions of videos via video converting (for the former) or provide alternative similar videos when requested videos are not available by using video recommendation (for the latter). However, existing work in this aspect has utilized these two techniques separately, which largely limit their capabilities in providing improved video services. In this article, we study how to jointly utilize these two techniques in edge caching for improved caching performance. The objective is to maximally reduce the video delivery delay while satisfying users’ requirements. We first formulate the optimal video caching problem in this case and derive its NP-hardness. We, then, propose an effective transcoding- and recommending-based caching algorithm (TRBA). The TRBA works in a greedy manner to iteratively buffer the most valuable video versions, one video version each time, until no more video version or cache space is available. We define the value of a video version as the reduced delivery delay if this version were buffered divided by the extra cache space required for its buffering. The computational complexity of TRBA is deduced as <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$O(|V|^3|Q|^3)$</tex-math></inline-formula> , where <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$|V|$</tex-math></inline-formula> and <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$|Q|$</tex-math></inline-formula> represent the total number of videos and the number of versions per video, respectively. Numerical results demonstrate that, compared with existing caching algorithms, TRBA can significantly improve the caching performance.

Enhanced Few-Shot Learning for Intrusion Detection in Railway Video Surveillance

Video surveillance is gaining increasing popularity to assist in railway intrusion detection in recent years. However, efficient and accurate intrusion detection remains a challenging issue due to: (a) limited sample number: only small sample size (or portion) of intrusive video frames is available; (b) high inter-scene dissimilarity: various railway track area scenes are captured by cameras installed in different landforms; (c) high intra-scene similarity: the video frames captured by an individual camera share a same background. In this paper, an efficient few-shot learning solution is developed to address the above issues. In particular, an enhanced model-agnostic meta-learner is trained using both the original video frames and segmented masks of track area extracted from the video. Moreover, theoretical analysis and engineering solutions are provided to cope with the highly similar video frames in the meta-model training phase. The proposed method is tested on realistic railway video dataset. Numerical results show that the enhanced meta-learner successfully adapts unseen scene with only few newly collected video frame samples, and its intrusion detection accuracy outperforms that of the standard randomly initialised supervised learning.

A STUDY OF ANXIETY EXPERIENCED BY EFL STUDENTS IN PRESENTING PROPOSAL SEMINARS AT ENGLISH STUDY PROGRAM MUHAMMADIYAH UNIVERSITY OF BENGKULU

This descriptive qualitative research aimed to find out the factors that cause anxiety in EFL students when presenting proposal seminars. A number of 20 students who had carried out proposal seminars participated as the subject of this research. Video and audio recording were conducted during the interviews to find out the factors of students’ anxiety during the presentation of the proposal seminars. The interviews revealed that, there were several factors that cause students’ anxiety in presenting proposal seminars, such as fear of failure, fear of negative criticism, lack of vocabulary, lack of grammar, poor pronunciation, fear of losing the thread of material, fear of being stopped, negative thinking, fear of making mistake, fear negative evaluation, and feel incompetent or appearing awkward in front of many people. It is suggested that EFL students who intend to conduct proposal seminars consider those factors to minimize anxiety. The finding of this research at the same time can be as a reference to create a better proposal seminar presentation. The last but not least, material mastery, presentation practices, watching some similar videos of seminars presentation, hard effort, and determination are truly essential factors contributing to the success of any proposal seminars presentation.&#x0D; &#x0D; Keywords: Anxiety, presentation, proposal seminar