Objective: The purpose of this study was to evaluate health education using videos and leaflets for preconception care (PCC) awareness among adolescent females up to six months after the health education. Methods: The...Objective: The purpose of this study was to evaluate health education using videos and leaflets for preconception care (PCC) awareness among adolescent females up to six months after the health education. Methods: The subjects were female university students living in the Kinki area. A longitudinal survey was conducted on 67 members in the intervention group, who received the health education, and 52 members in the control group, who did not receive the health education. The primary outcome measures were knowledge of PCC and the subscales of the Health Promotion Lifestyle Profile. Surveys were conducted before, after, and six months after the intervention in the intervention group, and an initial survey and survey six months later were conducted in the control group. Cochran’s Q test, Bonferroni’s multiple comparison test, and McNemar’s test were used to analyze the knowledge of PCC data. The Health Awareness, Nutrition, and Stress Management subscales of the Health Promotion Lifestyle Profile were analyzed by paired t-test, and comparisons between the intervention and control groups were performed using the two-way repeated measures analysis of variance. Results: In the intervention group of 67 people, the number of subjects who answered “correct” for five of the nine items concerning knowledge of PCC increased immediately after the health education (P = 0.006) but decreased for five items from immediately after the health education to six months later (P = 0.043). In addition, the number of respondents who answered “correct” for “low birth weight infants and future lifestyle-related diseases” (P = 0.016) increased after six months compared with before the health education. For the 52 subjects in the control group, there was no change in the number of subjects who answered “correct” for eight out of the nine items after six months. There was also no increase in scores for the Health Promotion Lifestyle Profile after six months for either the intervention or control group. Conclusion: Providing health education about PCC using videos and leaflets to adolescent females was shown to enhance the knowledge of PCC immediately after the education.展开更多
In the wave of internet culture,short videos have become an indispensable medium for social communication.The metaphorical hot words contained within them serve as a unique linguistic phenomenon that leads topics and ...In the wave of internet culture,short videos have become an indispensable medium for social communication.The metaphorical hot words contained within them serve as a unique linguistic phenomenon that leads topics and focuses attention,greatly enriching the expressive layers and rhetorical charm of short videos,and significantly enhancing the video’s theme orientation and emotional identification.This research aims to explore the relationship between the use of metaphorical Internet buzzwords in short videos and the thematic and emotional orientation.The study adopts a combination of qualitative and quantitative methods,taking 10 videos with over 10,000 likes posted by a well-known blogger on Xiaohongshu in 2024 as the research object,transcribing the text,forming research corpora,and conducting multi-dimensional cognitive analysis on them.The study shows that about half of short videos contain metaphorical hot words.Different types of metaphorical hot words can trigger different emotional reactions from fans,especially humorous metaphorical hot words that can stimulate fans’emotional identification and resonance.In addition,in terms of fan participation,videos using metaphorical hot words tend to attract more fan attention than those that do not:these videos not only attract more fans to watch and like,but also trigger more comments and sharing behaviors.In summary,short videos cleverly use metaphors to create internet hot words,significantly enhancing the video’s thematic guidance and emotional resonance,manifested in creating popular topics,clarifying guiding themes,enhancing content attractiveness,and stimulating strong emotional identification,thereby promoting interactive behaviors such as likes and shares.These findings provide a reference for research in related fields such as metaphor,communication studies,and sociology.展开更多
The Double Take column looks at a single topic from an African and Chinese perspective.This month,we explore how we can cope with the influence of short videos.
Short videos on social media have rapidly emerged as a powerful marketing tool for shaping consumer behavior.This comparative study investigates the impact of short videos on the purchasing behavior of young consumers...Short videos on social media have rapidly emerged as a powerful marketing tool for shaping consumer behavior.This comparative study investigates the impact of short videos on the purchasing behavior of young consumers(aged 18-35)in Hanoi and Taipei.Quantitative methods,including surveys,and experimental design,were employed in both cities,with a sample size of 200 respondents per location.Key influencing factors-including video content,product information,celebrity endorsement,viewer interaction,and perceived value-were systematically analyzed.The findings highlight both commonalities and contextual differences in how short videos influence purchasing behavior.This study offers practical implications for businesses and marketers targeting young consumers in Vietnam and Taiwan.展开更多
Video classification is an important task in video understanding and plays a pivotal role in intelligent monitoring of information content.Most existing methods do not consider the multimodal nature of the video,and t...Video classification is an important task in video understanding and plays a pivotal role in intelligent monitoring of information content.Most existing methods do not consider the multimodal nature of the video,and the modality fusion approach tends to be too simple,often neglecting modality alignment before fusion.This research introduces a novel dual stream multimodal alignment and fusion network named DMAFNet for classifying short videos.The network uses two unimodal encoder modules to extract features within modalities and exploits a multimodal encoder module to learn interaction between modalities.To solve the modality alignment problem,contrastive learning is introduced between two unimodal encoder modules.Additionally,masked language modeling(MLM)and video text matching(VTM)auxiliary tasks are introduced to improve the interaction between video frames and text modalities through backpropagation of loss functions.Diverse experiments prove the efficiency of DMAFNet in multimodal video classification tasks.Compared with other two mainstream baselines,DMAFNet achieves the best results on the 2022 WeChat Big Data Challenge dataset.展开更多
As a World Cultural Heritage site,the Beijing-Hangzhou Grand Canal has rich intangible cultural heritage(ICH)along its route.In the era of globalization and media convergence,using short videos to promote the canal’s...As a World Cultural Heritage site,the Beijing-Hangzhou Grand Canal has rich intangible cultural heritage(ICH)along its route.In the era of globalization and media convergence,using short videos to promote the canal’s ICH globally is important for internationalizing Chinese culture.This study uses cross-cultural communication theory,case analysis,and data research to examine the current status of short video dissemination of the canal’s ICH.It identifies core challenges in narrative techniques and cultural translation,and proposes a systematic optimization framework with five dimensions including content and platform.The findings offer both theoretical insights and practical guidance for the international promotion of ICH.展开更多
Automated recognition of violent activities from videos is vital for public safety,but often raises significant privacy concerns due to the sensitive nature of the footage.Moreover,resource constraints often hinder th...Automated recognition of violent activities from videos is vital for public safety,but often raises significant privacy concerns due to the sensitive nature of the footage.Moreover,resource constraints often hinder the deployment of deep learning-based complex video classification models on edge devices.With this motivation,this study aims to investigate an effective violent activity classifier while minimizing computational complexity,attaining competitive performance,and mitigating user data privacy concerns.We present a lightweight deep learning architecture with fewer parameters for efficient violent activity recognition.We utilize a two-stream formation of 3D depthwise separable convolution coupled with a linear self-attention mechanism for effective feature extraction,incorporating federated learning to address data privacy concerns.Experimental findings demonstrate the model’s effectiveness with test accuracies from 96%to above 97%on multiple datasets by incorporating the FedProx aggregation strategy.These findings underscore the potential to develop secure,efficient,and reliable solutions for violent activity recognition in real-world scenarios.展开更多
Objective:To explore the application effect of Problem-Based Learning(PBL)teaching method based on situational simulation videos in undergraduate teaching of internal medicine,and to provide practical basis for optimi...Objective:To explore the application effect of Problem-Based Learning(PBL)teaching method based on situational simulation videos in undergraduate teaching of internal medicine,and to provide practical basis for optimizing the undergraduate teaching mode of internal medicine and improving teaching quality.Methods:A total of 32 undergraduate students majoring in clinical medicine(Grade 2021)from Shanghai University of Medicine&Health Sciences were selected as the research subjects.They were divided into an experimental group and a control group by random number table method,with 16 students in each group.The control group adopted the traditional PBL teaching method,while the experimental group used the PBL teaching method based on situational simulation videos.After the teaching,the mastery of theoretical knowledge of students in the two groups was evaluated by examinations;a questionnaire survey was conducted to assess students’self-perceived improvement in clinical thinking,learning interest,self-directed learning ability and teamwork ability;statistical methods were used to analyze the data.Results:The scores of theoretical knowledge examination of students in the experimental group were significantly higher than those in the control group,and the difference was statistically significant(p<0.05).In terms of self-evaluation,the experimental group showed better performance than the control group in the cultivation of clinical thinking,learning interest and selfdirected learning ability,with statistically significant differences(p<0.05);however,there was no statistically significant difference in the self-evaluation of teamwork ability between the two groups(p>0.05).Conclusion:The PBL teaching method based on situational simulation videos can effectively improve students’level of theoretical knowledge,enhance their clinical thinking,learning interest and self-directed learning ability in undergraduate teaching of internal medicine,and is worthy of further promotion and application in undergraduate teaching of internal medicine.展开更多
Detecting feature points on the human body in video frames is a key step for tracking human movements. There have been methods developed that leverage models of human pose and classification of pixels of the body imag...Detecting feature points on the human body in video frames is a key step for tracking human movements. There have been methods developed that leverage models of human pose and classification of pixels of the body image. Yet, occlusion and robustness are still open challenges. In this paper, we present an automatic, model-free feature point detection and action tracking method using a time-of-flight camera. Our method automatically detects feature points for movement abstraction. To overcome errors caused by miss-detection and occlusion, a refinement method is devised that uses the trajectory of the feature points to correct the erroneous detections. Experiments were conducted using videos acquired with a Microsoft Kinect camera and a publicly available video set and comparisons were conducted with the state-of-the-art methods. The results demonstrated that our proposed method delivered improved and reliable performance with an average accuracy in the range of 90 %.The trajectorybased refinement also demonstrated satisfactory effectiveness that recovers the detection with a success rate of 93.7 %. Our method processed a frame in an average time of 71.1 ms.展开更多
Nowadays,people use online resources such as educational videos and courses.However,such videos and courses are mostly long and thus,summarizing them will be valuable.The video contents(visual,audio,and subtitles)coul...Nowadays,people use online resources such as educational videos and courses.However,such videos and courses are mostly long and thus,summarizing them will be valuable.The video contents(visual,audio,and subtitles)could be analyzed to generate textual summaries,i.e.,notes.Videos’subtitles contain significant information.Therefore,summarizing subtitles is effective to concentrate on the necessary details.Most of the existing studies used Term Frequency-Inverse Document Frequency(TF-IDF)and Latent Semantic Analysis(LSA)models to create lectures’summaries.This study takes another approach and applies LatentDirichlet Allocation(LDA),which proved its effectiveness in document summarization.Specifically,the proposed LDA summarization model follows three phases.The first phase aims to prepare the subtitle file for modelling by performing some preprocessing steps,such as removing stop words.In the second phase,the LDA model is trained on subtitles to generate the keywords list used to extract important sentences.Whereas in the third phase,a summary is generated based on the keywords list.The generated summaries by LDA were lengthy;thus,a length enhancement method has been proposed.For the evaluation,the authors developed manual summaries of the existing“EDUVSUM”educational videos dataset.The authors compared the generated summaries with the manual-generated outlines using two methods,(i)Recall-Oriented Understudy for Gisting Evaluation(ROUGE)and(ii)human evaluation.The performance of LDA-based generated summaries outperforms the summaries generated by TF-IDF and LSA.Besides reducing the summaries’length,the proposed length enhancement method did improve the summaries’precision rates.Other domains,such as news videos,can apply the proposed method for video summarization.展开更多
A new wipe transition detection approach was proposed. By analyzing the spatial-temporal characteristics of an ideal wipe production model, the concept of wipe transition strip (TS) was introduced. The macroblock type...A new wipe transition detection approach was proposed. By analyzing the spatial-temporal characteristics of an ideal wipe production model, the concept of wipe transition strip (TS) was introduced. The macroblock type information of P-frames is used to extract TS regions. An improved TS region accumulation technique is performed for detecting and verifying wipe transitions. The experimental results indicate that the proposed approach is capable of detecting various wipe transitions quickly and accurately.展开更多
Pulse rate is one of the important characteristics of traditional Chinese medicine pulse diagnosis,and it is of great significance for determining the nature of cold and heat in diseases.The prediction of pulse rate b...Pulse rate is one of the important characteristics of traditional Chinese medicine pulse diagnosis,and it is of great significance for determining the nature of cold and heat in diseases.The prediction of pulse rate based on facial video is an exciting research field for getting palpation information by observation diagnosis.However,most studies focus on optimizing the algorithm based on a small sample of participants without systematically investigating multiple influencing factors.A total of 209 participants and 2,435 facial videos,based on our self-constructed Multi-Scene Sign Dataset and the public datasets,were used to perform a multi-level and multi-factor comprehensive comparison.The effects of different datasets,blood volume pulse signal extraction algorithms,region of interests,time windows,color spaces,pulse rate calculation methods,and video recording scenes were analyzed.Furthermore,we proposed a blood volume pulse signal quality optimization strategy based on the inverse Fourier transform and an improvement strategy for pulse rate estimation based on signal-to-noise ratio threshold sliding.We found that the effects of video estimation of pulse rate in the Multi-Scene Sign Dataset and Pulse Rate Detection Dataset were better than in other datasets.Compared with Fast independent component analysis and Single Channel algorithms,chrominance-based method and plane-orthogonal-to-skin algorithms have a more vital anti-interference ability and higher robustness.The performances of the five-organs fusion area and the full-face area were better than that of single sub-regions,and the fewer motion artifacts and better lighting can improve the precision of pulse rate estimation.展开更多
Although compressive measurements save data storage and bandwidth usage, they are difficult to be used directly for target tracking and classification without pixel reconstruction. This is because the Gaussian random ...Although compressive measurements save data storage and bandwidth usage, they are difficult to be used directly for target tracking and classification without pixel reconstruction. This is because the Gaussian random matrix destroys the target location information in the original video frames. This paper summarizes our research effort on target tracking and classification directly in the compressive measurement domain. We focus on one particular type of compressive measurement using pixel subsampling. That is, original pixels in video frames are randomly subsampled. Even in such a special compressive sensing setting, conventional trackers do not work in a satisfactory manner. We propose a deep learning approach that integrates YOLO (You Only Look Once) and ResNet (residual network) for multiple target tracking and classification. YOLO is used for multiple target tracking and ResNet is for target classification. Extensive experiments using short wave infrared (SWIR), mid-wave infrared (MWIR), and long-wave infrared (LWIR) videos demonstrated the efficacy of the proposed approach even though the training data are very scarce.展开更多
Recent research advances in implicit neural representation have shown that a wide range of video data distributions are achieved by sharing model weights for Neural Representation for Videos(NeRV).While explicit metho...Recent research advances in implicit neural representation have shown that a wide range of video data distributions are achieved by sharing model weights for Neural Representation for Videos(NeRV).While explicit methods exist for accurately embedding ownership or copyright information in video data,the nascent NeRV framework has yet to address this issue comprehensively.In response,this paper introduces MarkINeRV,a scheme designed to embed watermarking information into video frames using an invertible neural network watermarking approach to protect the copyright of NeRV,which models the embedding and extraction of watermarks as a pair of inverse processes of a reversible network and employs the same network to achieve embedding and extraction of watermarks.It is just that the information flow is in the opposite direction.Additionally,a video frame quality enhancement module is incorporated to mitigate watermarking information losses in the rendering process and the possibility ofmalicious attacks during transmission,ensuring the accurate extraction of watermarking information through the invertible network’s inverse process.This paper evaluates the accuracy,robustness,and invisibility of MarkINeRV through multiple video datasets.The results demonstrate its efficacy in extracting watermarking information for copyright protection of NeRV.MarkINeRV represents a pioneering investigation into copyright issues surrounding NeRV.展开更多
This paper proposes a thorough scheme, by virtue of camera zooming descriptor with two-level threshold, to automatically retrieve close-ups directly from moving picture experts group （MPEG） compressed videos based o...This paper proposes a thorough scheme, by virtue of camera zooming descriptor with two-level threshold, to automatically retrieve close-ups directly from moving picture experts group （MPEG） compressed videos based on camera motion analysis. A new algorithm for fast camera motion estimation in compressed domain is presented. In the retrieval process, camera-motion-based semantic retrieval is built. To improve the coverage of the proposed scheme, close-up retrieval in all kinds of videos is investigated. Extensive experiments illustrate that the proposed scheme provides promising retrieval results under real-time and automatic application scenario.展开更多
Although the American Academy of Pediatrics （AAP） recommends no ＂screen time＂ for children under age of two, parents in the US are ignoring this edict. Routinely, mothers are exposing their babies to media crafted...Although the American Academy of Pediatrics （AAP） recommends no ＂screen time＂ for children under age of two, parents in the US are ignoring this edict. Routinely, mothers are exposing their babies to media crafted specifically for this age group. This study seeks to ascertain the reason. What beliefs do mothers hold regarding the marketing of such media and the expected benefits to their young ones？ How does the use of videos such as Baby Einstein benefit the mother？ Although mothers reported that video creators want them to think the videos are educational, they are skeptical. However, they continue to let babies watch this ＂safe＂ content. Among the 28 mothers interviewed for this project, only four claimed to always watch with their child; the remainder used ＂video time＂ to do household chores. Overwhelmingly, mothers heard positive comments about videos from fellow parents, but rarely heard from their pediatricians about possible negative effects on the under-two＇ s.展开更多
This research is about the relationship between Nigerian home videos production, women and cultural ideologies. It is general agreed that there is a sexist problem which has dominated the entire mass media. The study ...This research is about the relationship between Nigerian home videos production, women and cultural ideologies. It is general agreed that there is a sexist problem which has dominated the entire mass media. The study researches that an impact assessment of the images of women in Nigerian home videos is designed to examine the sway Nigerian home videos portrayal of women have on women＇s position and status in the society. The study also investigates the influence of home videos on women＇s and girl＇s perception of themselves and its effect on their development potentials. With 300 respondents drawn from a select range of home videos viewers, a survey research was designed using Awka-urban, Capital of Anambra State, Nigeria as the research area and finds a negative perception of women as regards their image portrayal in the home videos by the viewers. However, this image portrayal has a negative effect on the development potentials of women and that of girl child and as well reflects on how women are seen and treated in Nigerian society.展开更多
This article highlights the importance of complementing classes through educational videos, especially in disciplines exclusively with lectures. This proposition is exemplified through basic concepts in alternating cu...This article highlights the importance of complementing classes through educational videos, especially in disciplines exclusively with lectures. This proposition is exemplified through basic concepts in alternating current for both single-phase and three-phase circuits, which are critical in the formation of electrical engineers, mechanics, chemists, etc. The main objective of conducting educational videos is to make learning more attractive and stimulate interest in acquiring the knowledge of certain topics, given their importance in professional life in different engineering areas. The videos, filmed in laboratory and of short duration, aim to complement and consolidate the content taught in the classroom lectures.展开更多
Audio description(AD),unlike interlingual translation and interpretation,is subject to unique constraints as a spoken text.Facilitated by AD,educational videos on COVID-19 anti-virus measures are made accessible to th...Audio description(AD),unlike interlingual translation and interpretation,is subject to unique constraints as a spoken text.Facilitated by AD,educational videos on COVID-19 anti-virus measures are made accessible to the visually disadvantaged.In this study,a corpus of AD of COVID-19 educational videos is developed,named“Audio Description Corpus of COVID-19 Educational Videos”(ADCCEV).Drawing on the model of Textual and Linguistic Audio Description Matrix(TLADM),this paper aims to identify the linguistic and textual idiosyncrasies of AD themed on COVID-19 response released by the New Zealand Government.This study finds that linguistically,the AD script uses a mix of complete sentences and phrases,the majority being in Present Simple tense.Present participles and the“with”structure are used for brevity.Vocabulary is diverse,with simpler words for animated explainers.Third-person pronouns are common in educational videos.Color words are a salient feature of AD,where“yellow”denotes urgency,and“red”indicates importance,negativity,and hostility.On textual idiosyncrasies,coherence is achieved through intermodal components that align with the video’s mood and style.AD style varies depending on the video’s purpose,from informative to narrative or expressive.展开更多
文摘Objective: The purpose of this study was to evaluate health education using videos and leaflets for preconception care (PCC) awareness among adolescent females up to six months after the health education. Methods: The subjects were female university students living in the Kinki area. A longitudinal survey was conducted on 67 members in the intervention group, who received the health education, and 52 members in the control group, who did not receive the health education. The primary outcome measures were knowledge of PCC and the subscales of the Health Promotion Lifestyle Profile. Surveys were conducted before, after, and six months after the intervention in the intervention group, and an initial survey and survey six months later were conducted in the control group. Cochran’s Q test, Bonferroni’s multiple comparison test, and McNemar’s test were used to analyze the knowledge of PCC data. The Health Awareness, Nutrition, and Stress Management subscales of the Health Promotion Lifestyle Profile were analyzed by paired t-test, and comparisons between the intervention and control groups were performed using the two-way repeated measures analysis of variance. Results: In the intervention group of 67 people, the number of subjects who answered “correct” for five of the nine items concerning knowledge of PCC increased immediately after the health education (P = 0.006) but decreased for five items from immediately after the health education to six months later (P = 0.043). In addition, the number of respondents who answered “correct” for “low birth weight infants and future lifestyle-related diseases” (P = 0.016) increased after six months compared with before the health education. For the 52 subjects in the control group, there was no change in the number of subjects who answered “correct” for eight out of the nine items after six months. There was also no increase in scores for the Health Promotion Lifestyle Profile after six months for either the intervention or control group. Conclusion: Providing health education about PCC using videos and leaflets to adolescent females was shown to enhance the knowledge of PCC immediately after the education.
文摘In the wave of internet culture,short videos have become an indispensable medium for social communication.The metaphorical hot words contained within them serve as a unique linguistic phenomenon that leads topics and focuses attention,greatly enriching the expressive layers and rhetorical charm of short videos,and significantly enhancing the video’s theme orientation and emotional identification.This research aims to explore the relationship between the use of metaphorical Internet buzzwords in short videos and the thematic and emotional orientation.The study adopts a combination of qualitative and quantitative methods,taking 10 videos with over 10,000 likes posted by a well-known blogger on Xiaohongshu in 2024 as the research object,transcribing the text,forming research corpora,and conducting multi-dimensional cognitive analysis on them.The study shows that about half of short videos contain metaphorical hot words.Different types of metaphorical hot words can trigger different emotional reactions from fans,especially humorous metaphorical hot words that can stimulate fans’emotional identification and resonance.In addition,in terms of fan participation,videos using metaphorical hot words tend to attract more fan attention than those that do not:these videos not only attract more fans to watch and like,but also trigger more comments and sharing behaviors.In summary,short videos cleverly use metaphors to create internet hot words,significantly enhancing the video’s thematic guidance and emotional resonance,manifested in creating popular topics,clarifying guiding themes,enhancing content attractiveness,and stimulating strong emotional identification,thereby promoting interactive behaviors such as likes and shares.These findings provide a reference for research in related fields such as metaphor,communication studies,and sociology.
文摘The Double Take column looks at a single topic from an African and Chinese perspective.This month,we explore how we can cope with the influence of short videos.
文摘Short videos on social media have rapidly emerged as a powerful marketing tool for shaping consumer behavior.This comparative study investigates the impact of short videos on the purchasing behavior of young consumers(aged 18-35)in Hanoi and Taipei.Quantitative methods,including surveys,and experimental design,were employed in both cities,with a sample size of 200 respondents per location.Key influencing factors-including video content,product information,celebrity endorsement,viewer interaction,and perceived value-were systematically analyzed.The findings highlight both commonalities and contextual differences in how short videos influence purchasing behavior.This study offers practical implications for businesses and marketers targeting young consumers in Vietnam and Taiwan.
基金Fundamental Research Funds for the Central Universities,China(No.2232021A-10)National Natural Science Foundation of China(No.61903078)+1 种基金Shanghai Sailing Program,China(No.22YF1401300)Natural Science Foundation of Shanghai,China(No.20ZR1400400)。
文摘Video classification is an important task in video understanding and plays a pivotal role in intelligent monitoring of information content.Most existing methods do not consider the multimodal nature of the video,and the modality fusion approach tends to be too simple,often neglecting modality alignment before fusion.This research introduces a novel dual stream multimodal alignment and fusion network named DMAFNet for classifying short videos.The network uses two unimodal encoder modules to extract features within modalities and exploits a multimodal encoder module to learn interaction between modalities.To solve the modality alignment problem,contrastive learning is introduced between two unimodal encoder modules.Additionally,masked language modeling(MLM)and video text matching(VTM)auxiliary tasks are introduced to improve the interaction between video frames and text modalities through backpropagation of loss functions.Diverse experiments prove the efficiency of DMAFNet in multimodal video classification tasks.Compared with other two mainstream baselines,DMAFNet achieves the best results on the 2022 WeChat Big Data Challenge dataset.
基金sponsored by the 2024 annual special research project on humanities exchange initiated by the Sino-Foreign Humanities Exchange Center of the Ministry of Education and the Sino-Foreign Humanities Exchange Research Institute in the cultural tourism industry(CCIPEWHLY2024034).
文摘As a World Cultural Heritage site,the Beijing-Hangzhou Grand Canal has rich intangible cultural heritage(ICH)along its route.In the era of globalization and media convergence,using short videos to promote the canal’s ICH globally is important for internationalizing Chinese culture.This study uses cross-cultural communication theory,case analysis,and data research to examine the current status of short video dissemination of the canal’s ICH.It identifies core challenges in narrative techniques and cultural translation,and proposes a systematic optimization framework with five dimensions including content and platform.The findings offer both theoretical insights and practical guidance for the international promotion of ICH.
基金Supported by the Research Chair of Online Dialogue and Cultural Communication,King Saud University,Saudi Arabia.
文摘Automated recognition of violent activities from videos is vital for public safety,but often raises significant privacy concerns due to the sensitive nature of the footage.Moreover,resource constraints often hinder the deployment of deep learning-based complex video classification models on edge devices.With this motivation,this study aims to investigate an effective violent activity classifier while minimizing computational complexity,attaining competitive performance,and mitigating user data privacy concerns.We present a lightweight deep learning architecture with fewer parameters for efficient violent activity recognition.We utilize a two-stream formation of 3D depthwise separable convolution coupled with a linear self-attention mechanism for effective feature extraction,incorporating federated learning to address data privacy concerns.Experimental findings demonstrate the model’s effectiveness with test accuracies from 96%to above 97%on multiple datasets by incorporating the FedProx aggregation strategy.These findings underscore the potential to develop secure,efficient,and reliable solutions for violent activity recognition in real-world scenarios.
基金Teacher Teaching and Educational Research Project of Shanghai University of Medicine and Health Sciences in 2024(Project No.:CFDY20240035)。
文摘Objective:To explore the application effect of Problem-Based Learning(PBL)teaching method based on situational simulation videos in undergraduate teaching of internal medicine,and to provide practical basis for optimizing the undergraduate teaching mode of internal medicine and improving teaching quality.Methods:A total of 32 undergraduate students majoring in clinical medicine(Grade 2021)from Shanghai University of Medicine&Health Sciences were selected as the research subjects.They were divided into an experimental group and a control group by random number table method,with 16 students in each group.The control group adopted the traditional PBL teaching method,while the experimental group used the PBL teaching method based on situational simulation videos.After the teaching,the mastery of theoretical knowledge of students in the two groups was evaluated by examinations;a questionnaire survey was conducted to assess students’self-perceived improvement in clinical thinking,learning interest,self-directed learning ability and teamwork ability;statistical methods were used to analyze the data.Results:The scores of theoretical knowledge examination of students in the experimental group were significantly higher than those in the control group,and the difference was statistically significant(p<0.05).In terms of self-evaluation,the experimental group showed better performance than the control group in the cultivation of clinical thinking,learning interest and selfdirected learning ability,with statistically significant differences(p<0.05);however,there was no statistically significant difference in the self-evaluation of teamwork ability between the two groups(p>0.05).Conclusion:The PBL teaching method based on situational simulation videos can effectively improve students’level of theoretical knowledge,enhance their clinical thinking,learning interest and self-directed learning ability in undergraduate teaching of internal medicine,and is worthy of further promotion and application in undergraduate teaching of internal medicine.
文摘Detecting feature points on the human body in video frames is a key step for tracking human movements. There have been methods developed that leverage models of human pose and classification of pixels of the body image. Yet, occlusion and robustness are still open challenges. In this paper, we present an automatic, model-free feature point detection and action tracking method using a time-of-flight camera. Our method automatically detects feature points for movement abstraction. To overcome errors caused by miss-detection and occlusion, a refinement method is devised that uses the trajectory of the feature points to correct the erroneous detections. Experiments were conducted using videos acquired with a Microsoft Kinect camera and a publicly available video set and comparisons were conducted with the state-of-the-art methods. The results demonstrated that our proposed method delivered improved and reliable performance with an average accuracy in the range of 90 %.The trajectorybased refinement also demonstrated satisfactory effectiveness that recovers the detection with a success rate of 93.7 %. Our method processed a frame in an average time of 71.1 ms.
文摘Nowadays,people use online resources such as educational videos and courses.However,such videos and courses are mostly long and thus,summarizing them will be valuable.The video contents(visual,audio,and subtitles)could be analyzed to generate textual summaries,i.e.,notes.Videos’subtitles contain significant information.Therefore,summarizing subtitles is effective to concentrate on the necessary details.Most of the existing studies used Term Frequency-Inverse Document Frequency(TF-IDF)and Latent Semantic Analysis(LSA)models to create lectures’summaries.This study takes another approach and applies LatentDirichlet Allocation(LDA),which proved its effectiveness in document summarization.Specifically,the proposed LDA summarization model follows three phases.The first phase aims to prepare the subtitle file for modelling by performing some preprocessing steps,such as removing stop words.In the second phase,the LDA model is trained on subtitles to generate the keywords list used to extract important sentences.Whereas in the third phase,a summary is generated based on the keywords list.The generated summaries by LDA were lengthy;thus,a length enhancement method has been proposed.For the evaluation,the authors developed manual summaries of the existing“EDUVSUM”educational videos dataset.The authors compared the generated summaries with the manual-generated outlines using two methods,(i)Recall-Oriented Understudy for Gisting Evaluation(ROUGE)and(ii)human evaluation.The performance of LDA-based generated summaries outperforms the summaries generated by TF-IDF and LSA.Besides reducing the summaries’length,the proposed length enhancement method did improve the summaries’precision rates.Other domains,such as news videos,can apply the proposed method for video summarization.
文摘A new wipe transition detection approach was proposed. By analyzing the spatial-temporal characteristics of an ideal wipe production model, the concept of wipe transition strip (TS) was introduced. The macroblock type information of P-frames is used to extract TS regions. An improved TS region accumulation technique is performed for detecting and verifying wipe transitions. The experimental results indicate that the proposed approach is capable of detecting various wipe transitions quickly and accurately.
基金supported by the Key Research Program of the Chinese Academy of Sciences(grant number ZDRW-ZS-2021-1-2).
文摘Pulse rate is one of the important characteristics of traditional Chinese medicine pulse diagnosis,and it is of great significance for determining the nature of cold and heat in diseases.The prediction of pulse rate based on facial video is an exciting research field for getting palpation information by observation diagnosis.However,most studies focus on optimizing the algorithm based on a small sample of participants without systematically investigating multiple influencing factors.A total of 209 participants and 2,435 facial videos,based on our self-constructed Multi-Scene Sign Dataset and the public datasets,were used to perform a multi-level and multi-factor comprehensive comparison.The effects of different datasets,blood volume pulse signal extraction algorithms,region of interests,time windows,color spaces,pulse rate calculation methods,and video recording scenes were analyzed.Furthermore,we proposed a blood volume pulse signal quality optimization strategy based on the inverse Fourier transform and an improvement strategy for pulse rate estimation based on signal-to-noise ratio threshold sliding.We found that the effects of video estimation of pulse rate in the Multi-Scene Sign Dataset and Pulse Rate Detection Dataset were better than in other datasets.Compared with Fast independent component analysis and Single Channel algorithms,chrominance-based method and plane-orthogonal-to-skin algorithms have a more vital anti-interference ability and higher robustness.The performances of the five-organs fusion area and the full-face area were better than that of single sub-regions,and the fewer motion artifacts and better lighting can improve the precision of pulse rate estimation.
文摘Although compressive measurements save data storage and bandwidth usage, they are difficult to be used directly for target tracking and classification without pixel reconstruction. This is because the Gaussian random matrix destroys the target location information in the original video frames. This paper summarizes our research effort on target tracking and classification directly in the compressive measurement domain. We focus on one particular type of compressive measurement using pixel subsampling. That is, original pixels in video frames are randomly subsampled. Even in such a special compressive sensing setting, conventional trackers do not work in a satisfactory manner. We propose a deep learning approach that integrates YOLO (You Only Look Once) and ResNet (residual network) for multiple target tracking and classification. YOLO is used for multiple target tracking and ResNet is for target classification. Extensive experiments using short wave infrared (SWIR), mid-wave infrared (MWIR), and long-wave infrared (LWIR) videos demonstrated the efficacy of the proposed approach even though the training data are very scarce.
基金supported by the National Natural Science Foundation of China,with Fund Numbers 62272478,62102451the National Defense Science and Technology Independent Research Project(Intelligent Information Hiding Technology and Its Applications in a Certain Field)and Science and Technology Innovation Team Innovative Research Project“Research on Key Technologies for Intelligent Information Hiding”with Fund Number ZZKY20222102.
文摘Recent research advances in implicit neural representation have shown that a wide range of video data distributions are achieved by sharing model weights for Neural Representation for Videos(NeRV).While explicit methods exist for accurately embedding ownership or copyright information in video data,the nascent NeRV framework has yet to address this issue comprehensively.In response,this paper introduces MarkINeRV,a scheme designed to embed watermarking information into video frames using an invertible neural network watermarking approach to protect the copyright of NeRV,which models the embedding and extraction of watermarks as a pair of inverse processes of a reversible network and employs the same network to achieve embedding and extraction of watermarks.It is just that the information flow is in the opposite direction.Additionally,a video frame quality enhancement module is incorporated to mitigate watermarking information losses in the rendering process and the possibility ofmalicious attacks during transmission,ensuring the accurate extraction of watermarking information through the invertible network’s inverse process.This paper evaluates the accuracy,robustness,and invisibility of MarkINeRV through multiple video datasets.The results demonstrate its efficacy in extracting watermarking information for copyright protection of NeRV.MarkINeRV represents a pioneering investigation into copyright issues surrounding NeRV.
基金This work was supported by European IST FP6 Research Programme as funded for the Integrated Project:LIVE(No.IST-4-027312).
文摘This paper proposes a thorough scheme, by virtue of camera zooming descriptor with two-level threshold, to automatically retrieve close-ups directly from moving picture experts group （MPEG） compressed videos based on camera motion analysis. A new algorithm for fast camera motion estimation in compressed domain is presented. In the retrieval process, camera-motion-based semantic retrieval is built. To improve the coverage of the proposed scheme, close-up retrieval in all kinds of videos is investigated. Extensive experiments illustrate that the proposed scheme provides promising retrieval results under real-time and automatic application scenario.
文摘Although the American Academy of Pediatrics （AAP） recommends no ＂screen time＂ for children under age of two, parents in the US are ignoring this edict. Routinely, mothers are exposing their babies to media crafted specifically for this age group. This study seeks to ascertain the reason. What beliefs do mothers hold regarding the marketing of such media and the expected benefits to their young ones？ How does the use of videos such as Baby Einstein benefit the mother？ Although mothers reported that video creators want them to think the videos are educational, they are skeptical. However, they continue to let babies watch this ＂safe＂ content. Among the 28 mothers interviewed for this project, only four claimed to always watch with their child; the remainder used ＂video time＂ to do household chores. Overwhelmingly, mothers heard positive comments about videos from fellow parents, but rarely heard from their pediatricians about possible negative effects on the under-two＇ s.
文摘This research is about the relationship between Nigerian home videos production, women and cultural ideologies. It is general agreed that there is a sexist problem which has dominated the entire mass media. The study researches that an impact assessment of the images of women in Nigerian home videos is designed to examine the sway Nigerian home videos portrayal of women have on women＇s position and status in the society. The study also investigates the influence of home videos on women＇s and girl＇s perception of themselves and its effect on their development potentials. With 300 respondents drawn from a select range of home videos viewers, a survey research was designed using Awka-urban, Capital of Anambra State, Nigeria as the research area and finds a negative perception of women as regards their image portrayal in the home videos by the viewers. However, this image portrayal has a negative effect on the development potentials of women and that of girl child and as well reflects on how women are seen and treated in Nigerian society.
文摘This article highlights the importance of complementing classes through educational videos, especially in disciplines exclusively with lectures. This proposition is exemplified through basic concepts in alternating current for both single-phase and three-phase circuits, which are critical in the formation of electrical engineers, mechanics, chemists, etc. The main objective of conducting educational videos is to make learning more attractive and stimulate interest in acquiring the knowledge of certain topics, given their importance in professional life in different engineering areas. The videos, filmed in laboratory and of short duration, aim to complement and consolidate the content taught in the classroom lectures.
文摘Audio description(AD),unlike interlingual translation and interpretation,is subject to unique constraints as a spoken text.Facilitated by AD,educational videos on COVID-19 anti-virus measures are made accessible to the visually disadvantaged.In this study,a corpus of AD of COVID-19 educational videos is developed,named“Audio Description Corpus of COVID-19 Educational Videos”(ADCCEV).Drawing on the model of Textual and Linguistic Audio Description Matrix(TLADM),this paper aims to identify the linguistic and textual idiosyncrasies of AD themed on COVID-19 response released by the New Zealand Government.This study finds that linguistically,the AD script uses a mix of complete sentences and phrases,the majority being in Present Simple tense.Present participles and the“with”structure are used for brevity.Vocabulary is diverse,with simpler words for animated explainers.Third-person pronouns are common in educational videos.Color words are a salient feature of AD,where“yellow”denotes urgency,and“red”indicates importance,negativity,and hostility.On textual idiosyncrasies,coherence is achieved through intermodal components that align with the video’s mood and style.AD style varies depending on the video’s purpose,from informative to narrative or expressive.
