Video Software Research Articles

Energy Consumption and Carbon Emissions of Modern Software Video Encoders

Energy Consumption and Carbon Emissions of Modern Software Video Encoders

Easter eggs: Signaling quality via intrinsic motivation

AbstractEaster eggs are initially hidden elements of a consumer experience that have little direct commercial benefit for the brand. While Easter eggs may have been present in video games and software since the 1970s, they are now found in more and more consumer products such as cars, fashion, and fast food. This work explores the possible motivations for brands to include Easter eggs in their experiences by testing their effects on consumers during the post-purchase experience. It is found that Easter eggs serve as a new type of quality signal and positively affect perceived quality. The positive effect of Easter eggs on perceived product quality appears to be mediated by increased perceived intrinsic motivation of the brand’s employees. One study on Amazon.com reviews data on video games, and three online experiments on fashion, candy, and cars lend support to these hypotheses.

The Impact of Pop Music on Teenagers' Music Aesthetics under Short Video

Popular music, also known as "popular music", has developed rapidly in China in recent years and is deeply loved by the public. With the popularity of smart phones and the development of the Internet, short video software has gradually emerged. The platform represented by Tiktok has brought a new path to the development of popular music. A batch of popular music that is popular with short videos has set off a boom in all age groups. Teenagers account for the largest proportion of Internet users. This paper briefly discusses the impact of short videos on teenagers and popular music, analyzes the aesthetic characteristics of teenagers' music, and takes Tiktok "Subject 3" as an example, the characteristics of popular music under the background of short videos and its positive aesthetic impact on teenagers, and provides reference and suggestions for cultivating teenagers' aesthetic appreciation of music.

College Students Online Love to Participate in the Promotion Activities

With the rapid development of big data, there are more and more consumption ways of online shopping online. As China's e-commerce platforms continue to expand, various e-commerce shopping festivals also emerge. At the same time, the competition among online businesses has become increasingly fierce, and different promotion means emerge in endlessly. Therefore, businesses should seize the opportunity, seize the opportunity, and study the vast consumer group of college students. College students are an emerging consumer group of online shopping software. Many college students will buy on impulse under the stimulation of various promotional activities. For example, after swiping discounts on TikTok, Kuaishou and other video software, they are easy to have the desire for impulse consumption. In addition, college students mainly show the continuity of purchase when buying goods. If they have a good experience in the process of buying goods, they may continue to buy products of the same brand, and will recommend the products to their friends and relatives. College students stand at the front of the consumption concept, easy to contact, but also easy to accept new things, consumption concept ahead and change relatively fast. Secondly, college students should pursue the practical ability brought by commodities more often. College students have now become one of the main forces of consumption. This paper takes the domestic online consumption environment as the research background, and through the review of questionnaires and literature, studies the influence of product promotion mode on the impulsive purchase of product promotion. his paper explores which kind of promotion method that college students love to participate in in online shopping in China. The consumption phenomenon of college students is expected to provide reference for merchants to carry out online shopping promotion.

Students' Attitude Towards Focused Educational Video Sharing Sites for Learning

This study is aimed to analyse the psychological factors, social, technological and institutional that influence students' attitudes to use and accept the focused educational video sharing site. The acceptance factors were studied based on the technology acceptance model (TAM). A series of learning software video tutorials in the form of screencast has been developed and uploaded to focused educational video sharing sites named LearnSoftware to be used in this study. A questionnaire has been used as an instrument to analyse the students' attitudes in acceptance of the site for educational purpose. Quantitative research method was used and data were collected from 294 students of Multimedia studies (major and minor) from 5 Public Higher Learning Institutions. Multiple regression analysis conducted found that psychological factors contributed the main influence towards the use of the focused educational video sharing site. In sum, the findings of this study are beneficial for institutions, students and lecturers, and video-sharing site developers in understanding learners’ behavior towards decision-making in accepting and using new technologies introduced.

Voices from the algorithm: Large language models in social research

Research on energy and society often relies on online data collection. In particular, there has been an increase in the use of online techniques such as video software for qualitative research since the pandemic. We suggest that the rapid growth in generative AI and Large Language Models such as Chat-GPT mean that they may be utilised by research participants; particularly in research where participants may be less knowledgeable about the topic under discussion, such as emerging energy technologies. Drawing on examples from recent research, we argue that social scientists need to be cautious in assuming that the voices of our participants are genuinely theirs.

Design and implementation of an Unmanned Aerial Vehicle (UAV) for image capture in enterprise farming

Unmanned aerial vehicle (UAV), also known as drone is one of the most interesting emerging technologies with a wide range of applications including agriculture, surveillance, security, search and rescue, mapping, farmland surveying, and wildlife conservation, among others. In Nigeria, UAV is gaining popularity in applications such as in social functions for taking both moving and static pictures, military and security, mapping and agriculture. In this work, an UAV was designed, some components produced by 3D printing, coupled and tested with certain level of local content in view. The UAV is a quadcopter equipped with a camera for real-time image capture of farmlands and it can perform autonomous missions by using global positioning system (GPS) waypoints. The weight of the quadcopter was approximately calculated and hence the electrical and mechanical components selected using a standard empirical design table. The thrust to weight ratio was set at 2:1. Autodesk Maya and Inventor software were used to design the frame in two parts: the frame arms on which the propellers are mounted and the central connecting part that links the four arms. The arms are made up of aluminum square pipes while the central connecting part for the arms was printed with a 3D printer (200 x 200 x 200 Wanhao duplicator i3) using PolyEthylene Terephthalate Glycol (PETG) Filament material of 1.75mm standard gauge. Material selection was based on material strength, cost and availability. NCH Debut video and image capture software was used to record live feeds from the UAV onboard camera. Functionality tests for lift, stability, yaw, roll, pitch, loiter, auto landing, return to launch, flight time, altitude/signal, auto mission using GPS waypoints were carried out with the completed UAV on a less windy day to avoid the influence of wind. It was generally observed that the UAV successfully took off the ground, gained stability, flew to over 100m height, captured aerial photographs of the land below it while on flight at the required height and landed safely. Cost saving advantage of 45.28% was achieved when compared to imported equivalent types.

Tech-Driven Transformation: Improving English Language Instruction With Technology

This article focuses on exploring the transformational impact of technology on English Language Teaching (ELT) in the 21st century. The progress of educational technology and its role is facing challenges confronted by traditional ELT methods. The technologies include virtual reality, audio listening tools, video software tools, grammar tech, mobile applications, and personalized learning. Utilizing technology in language education enhances instruction, practice, and evaluation, as per the World-Readiness Standards for Learning Languages. Technology can support language learners as they use the target language in an interactive, meaningful way. Language educators are responsible for the planning, instruction, assessment, and facilitation of any language course, influencing technology to support language learning. This article emphasizes the need of the significance of teachers’ professional development, digital literacy, and pedagogical training for effective technology incorporation. Augmented Reality (AR) and Virtual Reality (VR) technologies are revolutionizing language education by offering immersive and interactive experiences that engage learners in ways which are unimaginable. Finally, the article emphasizes that by implementing technology considerately, educators can produce inclusive and lively learning environments that empower learners with essential language skills for the digital age.

ЗАКОНОМЕРНОСТИ ПОКАЗАТЕЛЯ ТРАНСПОРТНОГО ЗАТОРА НА НЕКОТОРЫХ ПЕРЕСЕЧЕНИЯХ УЛИЧНО-ДОРОЖНОЙ СЕТИ

The average speed and density of road transport are used as indicators of the congestion situation, but do not allow tracking the evolution (stages of formatting, progressing, and vanishing) of traffic congestion. The authors proposed and justified a quantitative indicator of traffic congestion, which allows in an automated mode to identify the congestion situation on the urban road network using hardware and software video recording systems. The purpose of this study is due to the need to study the quantitative characteristics of the proposed indicator at characteristic intersections of urban roads, which will allow us to develop scientifically based recommendations for predicting congestion situations, substantiating, and making optimal decisions on measures to promptly eliminate traffic congestion. The object of study is the traffic flow at three types of intersections of the Perm city road network, equipped with a photo and video recording software and hardware complex. The subject of the study is the regularities of the evolution of the listed deterministic indicators of traffic flows, which can be used for operational forecasting of the formation, development, and elimination of traffic congestion. The theoretical and methodological approach is based on the methods of mathematical statistics used to process the results of observations of traffic flows at different types of intersections using a «sliding window», calculating the average daily value and standard deviation. The initial data were obtained with the help of hardware and software complexes for fixing violations of traffic rules installed on the street and road network of the Perm city. As a result of the study, the rational parameters of the «sliding window» were determined, ensuring the structuring of the traffic congestion indicator; the facts of the congestion situations formation were revealed; the features of the congestion evolution and the presence of problematic traffic directions for which it is advisable to change the traffic light regulation mode were determined. The theoretical and practical significance of the work consists in checking the operability of the proposed indicator and criterion of traffic congestion, which is of practical interest from the point of view of predicting anomalies in the movement of vehicles on the road network, adjusting the operating modes of traffic lights, etc. It is also possible to use the proposed traffic congestion indicator to assess the effectiveness of traffic light regulation on the Perm city road network. The direction of further research is to study the patterns of traffic congestion at intersections of the urban road network, of various types that are not included in this study.

The Impact of Short videos on People's Consumption Habits

This article aims to analyze and summarize the changes in consumption habits caused by short video users due to the influence of short video through the literature review and the research of short video software. At the same time, the different age groups of users are affected by short videos. This article analyzes the different marketing strategies and methods of introducing products between different short video platforms. And the influencing factors of short videos and users' personal responses are studied. In addition, this paper combines short video audiences and consumers' personal factors to analyze the impact of short videos on people's consumption behavior. While focusing on the analysis of the short video platform- -TikTok, it is also compared with other platforms. At the same time, the advantages and disadvantages of short video marketing are analyzed, because of the risks brought by false propaganda.

Application of Short Video Semantic Understanding Technology Based on Big Data Analysis in Education Management

With the emergence of short video and the development of mobile internet, short video software, such as TikTok and Kwai, has emerged. Based on the semantic understanding technology of teaching short videos, a teaching management platform was built to push healthy and positive short video for students' content in a targeted way. Taking the 21st grade students majoring in Chinese in Guizhou Normal University as an example, the authors discusses the effect of teaching management platform on college students. In this process, the following conclusions are drawn: (1) Among college students, the viewing rate of short videos has exceeded 95%, and short videos have become an indispensable entertainment for most college students. (2) Through short video semantic understanding technology and short video screening program, excellent short video can be effectively pushed to students. (3) The actual effect shows that the short video teaching management platform can effectively improve the values of the cultural level of students.

Transforming the Future of Furniture Woodworking Instruction Through VR-Enhanced Distance Teaching During the COVID-19 Pandemic

During the COVID-19 pandemic, distance teaching became the main solution, including for the furniture woodworking course at National Taipei University of Technology in Taipei, Taiwan, which relied on video and online software. However, this posed challenges for maintaining teaching quality and achieving objectives in technical practice courses. To address this, this study introduced remote technical guidance using VR in technical practice courses. This method combined distance-teaching and live dual-teacher broadcasts, allowing students to participate in real-time online discussions. During these broadcasts, instructors used VR to demonstrate operations on a virtual platform, explaining as they went along. Students could observe from the operator's perspective, gaining insights into furniture production processes. They also engaged in group interactions, assuming roles like technical operators, thereby mastering key furniture production concepts. This innovative teaching approach offered a solution that combined remote technical guidance with VR. It provided immediate teaching enhancements and problem-solving solutions in the post-COVID-19 era.

Transformer Neural Networks, Information Biology, and Alzheimer’s Disease

AbstractBackgroundAlzheimer’s disease affects one in ten people older than 65 years, with the prevalence expected to triple by 2030, together with commensurate increases in cost. A comprehensive causal model of Alzheimer’s disease etiology is lacking despite more than three decades of study. Modern computational methods provide a new approach to multiscalar biosystems by modeling neuropathology in its native three‐dimensional character in topological biophysics and quantum computational models.MethodThis work describes how an emerging standard in machine learning, responsible for the AlphaFold (protein folding structure) and Gato generalist agent projects, transformer neural networks, may be applied to the study of Alzheimer’s disease per proven results in bot text chat, image recognition and creation, video generation, software programming, and autonomy in robotics and driving. The self‐attention and self‐learning mechanisms of transformer neural networks are discussed in application to multifaceted Alzheimer’s disease data sets involving neuroimaging scans, whole human genome data, and blood and CSF biomarker data.ResultA machine learning‐based topological biophysics model of Alzheimer’s disease neuropathology hypothesis‐testing (misfolded proteins, gene expression, diabetes type‐3, and peptide immune system stimulation) is described.ConclusionThere is an opportunity to apply state‐of‐the‐art transformer neural network machine learning techniques to the automated analysis of large accruing data stores of Alzheimer’s information (imaging, genomic, proteomic, and self‐reported data) towards the causal understanding of the neuropathology.

Transformer Neural Networks, Information Biology, and Alzheimer’s Disease

AbstractBackgroundAlzheimer’s disease affects one in ten people older than 65 years, with the prevalence expected to triple by 2030, together with commensurate increases in cost. A comprehensive causal model of Alzheimer’s disease etiology is lacking despite more than three decades of study. Modern computational methods provide a new approach to multiscalar biosystems by modeling neuropathology in its native three‐dimensional character in topological biophysics and quantum computational models.MethodThis work describes how an emerging standard in machine learning, responsible for the AlphaFold (protein folding structure) and Gato generalist agent projects, transformer neural networks, may be applied to the study of Alzheimer’s disease per proven results in bot text chat, image recognition and creation, video generation, software programming, and autonomy in robotics and driving. The self‐attention and self‐learning mechanisms of transformer neural networks are discussed in application to multifaceted Alzheimer’s disease data sets involving neuroimaging scans, whole human genome data, and blood and CSF biomarker data.ResultA machine learning‐based topological biophysics model of Alzheimer’s disease neuropathology hypothesis‐testing (misfolded proteins, gene expression, diabetes type‐3, and peptide immune system stimulation) is described.ConclusionThere is an opportunity to apply state‐of‐the‐art transformer neural network machine learning techniques to the automated analysis of large accruing data stores of Alzheimer’s information (imaging, genomic, proteomic, and self‐reported data) towards the causal understanding of the neuropathology.

The application of immunosuppressants education video and instant messaging software to improve compliance in transplant recipients

The application of immunosuppressants education video and instant messaging software to improve compliance in transplant recipients

Views on sharing mental health data for research purposes: qualitative analysis of interviews with people with mental illness

BackgroundImproving the ways in which routinely-collected mental health data are shared could facilitate substantial advances in research and treatment. However, this process should only be undertaken in partnership with those who provide such data. Despite relatively widespread investigation of public perspectives on health data sharing more generally, there is a lack of research on the views of people with mental illness.MethodsTwelve people with lived experience of mental illness took part in semi-structured interviews via online video software. Participants had experience of a broad range of mental health conditions including anxiety, depression, schizophrenia, eating disorders and addiction. Interview questions sought to establish how participants felt about the use of routinely-collected health data for research purposes, covering different types of health data, what health data should be used for, and any concerns around its use.ResultsThematic analysis identified four overarching themes: benefits of sharing mental health data, concerns about sharing mental health data, safeguards, and data types. Participants were clear that health data sharing should facilitate improved scientific knowledge and better treatments for mental illness. There were concerns that data misuse could become another way in which individuals and society discriminate against people with mental illness, for example through insurance premiums or employment decisions. Despite this there was a generally positive attitude to sharing mental health data as long as appropriate safeguards were in place.ConclusionsThere was notable strength of feeling across participants that more should be done to reduce the suffering caused by mental illness, and that this could be partly facilitated by well-managed sharing of health data. The mental health research community could build on this generally positive attitude to mental health data sharing by following rigorous best practice tailored to the specific concerns of people with mental illness.

Study of the Acceptance and Purchase Behavior of College Students' Audience by Bilibili Video Insertion Advertising

With the advent of the 5G network era, the use of smart phones has been popularized, and various short video software platforms have risen rapidly. The short video platform gathers a large user group and a large number of ACG original video creators. In the Internet era, traffic monetization capabilities are strong, and advertisers are setting their sights on short video platforms, bringing new business to advertisers and content creators. This study takes the short video insertion advertisement of the B-station APP as the research object, and studies the factors of content creation in the video insertion advertisement from the aspects of audience acceptance willingness and purchase behavior. This paper takes the UTAUT model as the theoretical basis for research, and simplifies and modifies it according to the UTAUT model, and becomes entertaining, creative, willing to accept and purchase behavior. The research method is a questionnaire method, which collects data and draws conclusions....

Development of an Integrated Statistics E-Module with Flipbook and Augmented Reality

Numeration is an important aspect of learning mathematics. Numeration is the ability to apply mathematical symbols to solve everyday problems. The importance of numeration contradicts the conditions in the field, which show that students in the statistics class have not been able to solve problems related to numeracy properly due to a lack of multi-representational skills. This truth is evident from the opening observations made in statistics class revealed that, out of 37 pupils, only 12 were successful in converting verbal and graphic representations into symbolic ones to solve statistical issues correctly. In the meantime, 17 out of 25 students failed because they did not comprehend the issues represented graphically. The SPSS practice video barcode and software of studio.essemblrword.com has been used in statistical module development research to find a solution to this issue. All of these programs are integrated into e-modules, which are packaged in flipbook form. Define, design, develop, and disseminate steps of the 4-D model are used in the development process. In this study, a questionnaire was employed as a data gathering tool. Both qualitative and quantitative data were collected. The findings demonstrated that the produced module met the extremely feasible criteria for content feasibility (85.78%), linguistic feasibility (88.61%), presentation feasibility (84.82%), and visual feasibility (84.72%). Keywords: Statistic E-Module, Multiple Representation, Augmented Reality

Students’ technology acceptance of computer-based applications for analyzing animal behavior in an out-of-school lab

Behavioral biology is a field that students find fascinating. To get the most out of the various benefits of teaching it, a practical approach should be followed. One way to do this is to use video recordings of animals which are analyzed using various software. However, learners will only benefit from this approach if they choose to actually use the provided technology. Therefore, it is critical to survey learners’ acceptance towards the use of software in the field of behavioral biology. For this purpose, 171 students were questioned at an out-of-school student lab called “KILab.” By applying the Technology Acceptance Model (TAM), we investigated students’ acceptance of authentic behavior evaluation software and possible factors influencing it. In addition, potential effects of the student lab on attitudes toward artificial intelligence and technology affinity were examined. The results show a high technology acceptance toward the used software and a dependence of this on the factors technology affinity and acceptance toward artificial intelligence. Furthermore, the use of the software has a positive impact on the self-assessed technology affinity and attitude toward artificial intelligence.The study thus shows that the use of video recordings and software for behavior analysis is generally suitable for educational use and can be a possible extension of the practical implementation of behavioral science education.

Research on the User Experience of Infinite Up-scrolling on Chinese Short Video Software Douyin

Douyin/TikTok is a popular short-form video application popular around the globe. The infinite up-scrolling video stream system that it is using is applying to more and more diversified applications. This research focused on the infinite up-scrolling video stream systems influence on the Chinese user group and the public reaction towards it. A survey was conducted, and 145 valid answers were received. The questionnaire focused on the publics daily interaction with the up-scrolling system. Through the statistics received, it is shown that most people like the feeling caused by up-swiping, and they easily use it over time. This phenomenon is explained from the perspective of psychology. The psychology analysis also explained why people often spend more time in this system than they planned or expected. Meanwhile, there is a large percentage of the public using the up-scrolling system in applications that are primarily for other usages. The system was adopted into these applications later on through program updates. With this system, applications are able to make their users more dependent on them. Therefore, this system is getting more and more popular in all kinds of applications.