Motivasi Milenial Menonton Layanan Streaming

Ponsel cerdas semakin banyak digunakan untuk menonton subscription video-on-demand. Tingkat adopsi aktivitas ini pun sangat tinggi di kalangan kaum milenial di Indonesia. Ini memunculkan pertanyaan mengapa khalayak semakin terbiasa menonton SVOD di ponsel cerdas meski memiliki keterbatasan audiovisual dibandingkan televisi, laptop atau komputer. Penelitian ini bertujuan melihat apa kebutuhan-kebutuhan spesifik yang terpenuhi ketika khalayak mengonsumsi konten subscription video-on-demand (SVOD) melalui ponsel cerdas. Berlandaskan teori uses and gratifications, penelitian menggunakan pendekatan kualitatif dan strategi grounded theory. Berdasarkan wawancara dengan enam informan, ditemukan bahwa khalayak memiliki tipologi kebutuhan yakni informasi, mengisi waktu, pengalaman terkustomisasi dan media displacement. Muncul tipologi yang mengalami ekspansi yakni hiburan hedonistik/eudaimonik, pindah waktu/tempat, kenyamanan/relaksasi, dan pengalihan/pengalaman imersif. Sementara muncul tipologi yang belum ditemukan dalam penelitian sebelumnya, yaitu menonton maraton. Direkomendasikan untuk mengoperasionaliasikan tipologi-tipologi yang ditemukan secara kuantittif untuk penelitian selanjutnya. Smartphones are increasingly used to access videos, including subscription video-on-demand services. This is especially true among millennials, who are the primary adopters. This raises the question of why millennials watch SVOD through their smartphones when other wide-screened devices offer better audiovisual quality. This research aims to reveal the motivations satisfied by using uses and gratification theory through qualitative approach and grounded theory strategy. Based on in-depth interviews of six informants, we found classical UG typologies, namely Information and Passing Time, and typologies recurring in new media research, which are customized experienced and media displacement. The study also produced expanded typologies, including hedonistic/eudaimonic entertainment, time/place-shifting, comfort/relaxation, and diversion/immersive experience. Lastly, binge-watching was discovered to be an emergent typology. As this research analyzes data from one informant, the results cannot be generalized. Operationalizing these typologies by using a quantitative approach is recommended for future research.

New Visual Expression of Anime Film Based on Artificial Intelligence and Machine Learning Technology

With the improvement of material living standards, spiritual entertainment has become more and more important. As a more popular spiritual entertainment project, film and television entertainment is gradually receiving attention from people. However, in recent years, the film industry has developed rapidly, and the output of animation movies has also increased year by year. How to quickly and accurately find the user’s favorite movies in the huge amount of animation movie data has become an urgent problem. Based on the above background, the purpose of this article is to study the new visual expression of animation movies based on artificial intelligence and machine learning technology. This article takes the film industry’s informatization and intelligent development and upgrading as the background, uses computer vision and machine learning technology as the basis to explore new methods and new models for realizing film visual expression, and proposes relevant thinking to promote the innovative development of film visual expression from a strategic level. This article takes the Hollywood anime movie “Kung Fu Panda” as a sample and uses convolutional neural algorithms to study its new visual expression. The study found that after the parameters of the model were determined, the accuracy of the test set did not change much, all around 57%. This is of great significance for improving the audiovisual quality and creative standards of film works and promoting the healthy and sustainable development of the film industry.

Telemedicine during the COVID-19 pandemic

Aims The COVID-19 pandemic led to a swift adoption of telehealth in orthopaedic surgery. This study aimed to analyze the satisfaction of patients and surgeons with the rapid expansion of telehealth at this time within the division of adult reconstructive surgery at a major urban academic tertiary hospital. Methods A total of 334 patients underging arthroplasty of the hip or knee who completed a telemedicine visit between 30 March and 30 April 2020 were sent a 14-question survey, scored on a five-point Likert scale. Eight adult reconstructive surgeons who used telemedicine during this time were sent a separate 14-question survey at the end of the study period. Factors influencing patient satisfaction were determined using univariate and multivariate ordinal logistic regression modelling. Results A total of 68 patients (20.4%) and 100% of the surgeons completed the surveys. Patients were “Satisfied” with their telemedicine visits (4.10/5.00 (SD 0.98)) and 19 (27.9%) would prefer telemedicine to in-person visits in the absence of COVID-19. Multivariate ordinal logistic regression modelling revealed that patients were more likely to be satisfied if their surgeon effectively responded to their questions or concerns (odds ratio (OR) 3.977; 95% confidence interval (CI) 1.260 to 13.190; p = 0.019) and if their visit had a high audiovisual quality (OR 2.46; 95% CI 1.052 to 6.219; p = 0.042). Surgeons were “Satisfied” with their telemedicine experience (3.63/5.00 (SD 0.92)) and were “Fairly Confident” (4.00/5.00 (SD 0.53)) in their diagnostic accuracy despite finding the physical examinations to be only “Slightly Effective” (1.88/5.00 (SD 0.99)). Most adult reconstructive surgeons, seven of eight (87.5%) would continue to use telemedicine in the future. Conclusion Telemedicine emerged as a valuable tool during the COVID-19 pandemic. Patients undergoing arthroplasty and their surgeons were satisfied with telemedicine and see a role for its use after the pandemic. The audiovisual quality and the responsiveness of physicians to the concerns of patients determine their satisfaction. Future investigations should focus on improving the physical examination of patients through telemedicine and strategies for its widespread implementation. Cite this article: Bone Joint J 2021;103-B(6 Supple A):196–204.

Assessment of QoE for Video and Audio in WebRTC Applications Using Full-Reference Models

WebRTC is a set of standard technologies that allows exchanging video and audio in real time on the Web. As with other media-related applications, the user-perceived audiovisual quality can be estimated using Quality of Experience (QoE) measurements. This paper analyses the behavior of different objective Full-Reference (FR) models for video and audio in WebRTC applications. FR models calculate the video and audio quality by comparing some original media reference with the degraded signal. To compute these models, we have created an open-source benchmark in which different types of reference media inputs are sent browser to browser while simulating different kinds of network conditions in terms of packet loss and jitter. Our benchmark provides recording capabilities of the impairment WebRTC streams. Then, we use different existing FR metrics for video (VMAF, VIFp, SSIM, MS-SSIM, PSNR, PSNR-HVS, and PSNR-HVS-M) and audio (PESQ, ViSQOL, and POLQA) recordings together with their references. Moreover, we use the same recordings to carry out a subjective analysis in which real users rate the video and audio quality using a Mean Opinion Score (MOS). Finally, we calculate the correlations between the objective and subjective results to find the objective models that better correspond with the subjective outcome, which is considered the ground truth QoE. We find that some of the studied objective models, such as VMAF, VIFp, and POLQA, show a strong correlation with the subjective results in packet loss scenarios.