Photographs Of People Research Articles

Content Analysis of Human Papilloma Virus Vaccine-Related Videos on YouTube in Japan

This study aimed to describe the YouTube content on Human Papilloma Virus (HPV) vaccines by analyzing the related Japanese videos in context of the account characteristics, attitude toward the vaccine, and thumbnail characteristics. Relevant videos with keywords “HPV vaccine” and “cervical cancer vaccine” uploaded before November 11, 2021 were collected and coded. The findings showed that as of November 11, 2021, positive and negative attitude videos regarding HPV vaccines accounted for approximately 44% of Japanese YouTube videos. In the year 2013, an increase in negative videos was observed, while from 2019 onwards, majority of the videos uploaded showed positive attitudes toward the vaccine. Videos with negative tones generally used the term "cervical cancer vaccines.” Most negative videos were uploaded by individual accounts, whereas all videos uploaded by medical workers were positive or neutral. Only four videos mentioned side effect compensation. The most frequently used thumbnails were photographs of people who appeared in the videos. Compared to English YouTube, there are fewer anti-vaccine videos in Japan, and there is also a lack of videos uploaded by credible authorities. Future research focusing on other platforms and the accuracy of video content should be included.

Design and Development of Indian Sign Language Character Recognition System

The purpose of this study is to look into the challenges involved in categorizing Indian Sign Language (ISL) characters. While a lot of research has been done in the related field of American Sign Language (ASL), not as much has been done with ISL. Lack of standard datasets, obscured traits, and variance in language with geography are the key barriers that have hindered much ISL research. Our study aims to progress this field by collecting a dataset from a deaf school and applying various feature extraction techniques to extract useful information, which is then input into a range of supervised learning algorithms. Our current results for each approach include four fold cross-validation. What sets our work apart from earlier research is that the validation set in our four-fold cross-validation contains photographs of people who are not the same people as those in the training set. Hand gestures and signs are used by those with speech impairments to communicate. Understanding what they're trying to say is challenging for the average person. Though extremely uncommon, there are many systems that convert data to Hindi. Therefore, it is imperative to implement a system that enables the general public to understand and interpret all signals, gestures, and communications. It will close the communication gap that exists between normal people and those who have speech difficulty. The two primary research approaches centered on human-computer interaction are sign language recognition and learning. Multiple sensors are required in order for data flow to be understood in sign language. This research paper focuses on the development of a Hindi-language training tool that can detect images and interpret what someone else is trying to say to persons who have speech impairments. Keywords: Indian Sign Language (ISL), American Sign Language (ASL), Feature Extraction, Supervised learning, Sign Language, etc.

Perceptual estimates of the physical attributes of people in photographs

Perceptual estimates of the physical attributes of people in photographs

Improving face morph detection with the pairs training effect

AbstractIt is becoming increasingly common for face morphs (weighted combinations of two people's photographs) to be submitted for inclusion in an official document, such as a passport. These images may sufficiently resemble both individuals that they can be used by either person in a ‘fraudulently obtained genuine’ document. Problematically, people are poor at detecting face morphs and there is limited evidence that this can be improved. Here, we tested whether the ‘pairs training effect’ (working in pairs, which we know improves unfamiliar face matching) can improve face morph detection. We found morph detection was more accurate when working in a pair. Further, the lower performer in the pair maintained this benefit when completing the task again individually. We conclude that the pairs training effect translates to face morph detection, and these findings have important implications for improving the detection of face morphs at the initial application stage.

The Relationship between Plastic Surgery Residency Instagram Characteristics and Doximity Rank

Background: Social media provides unique insight into the facilities, personnel, and culture of plastic surgery residency programs. Applicants can gain a more holistic view of programs based on their social media accounts. This study aims to evaluate the relationship between the popularity of a program's Instagram account and the program's Doximity ranking and to investigate the factors which contribute to greater viewership, with a special focus on diversity. Methods: Using Doximity's 2021-2022 Residency Navigator, a list of all integrated plastic surgery residency programs was obtained, and their social media accounts were documented. Instagram accounts were analyzed for metrics, post content, and website links. A 15-month period of posts was analyzed, then grouped into eight categories. Diversity was assessed using average Fitzpatrick skin type for each post containing photographs of people. Results: Of the 88 programs, 85 (96.6%) had an Instagram account at the time of analysis. Analysis of Instagram post content found that personnel and social function posts had significantly more likes than other categories. Posts with average Fitzpatrick type greater than or equal to III also had significantly more likes. Linear regression demonstrated a positive relationship between higher Doximity rank and number of followers; however, there was no clear relationship between rank and posts per week or engagement score. Conclusions: Plastic surgery social media accounts may make a positive impact on followers. It is important to understand the factors that can increase engagement and broaden viewership. Tailoring posts based on content popularity and highlighting diversity may help to accomplish these goals.

Interview with Chris Taylor, curator of Shifting Borders: A Journey to the Centre of Our World(s)1

Shifting Borders exhibits ‘traces’ of human mobility across millennia: of exploratory journeys, forced migrations, exilic arrivals at foreign lands and artistic schematizations of them based on memory and experience. The traces assume the form of maps, passports, photographs of people and locations, as well as actual diaries of movement produced by those who move or by institutions who regulate their movements. Crafted as a form of pilgrimage to these stories, the exhibition transcends binary understandings of hospitality as an inviolable norm and/or a secular pact conforming with the commercial rules of catering for strangers. Instead, the presentation of items in clusters produces variations of story-telling as a tribute to the presence of human otherness. Featuring styles of inscription and creative staging of particular mobility events, Shifting Borders showcases forms of movement vis-à-vis (‘psychic centres’): homes and homelands, memories of uprooting but also the excitement of travel and exploration in and of unknown territories. The exhibition’s simulation of such movements transforms artistic pilgrimage to a method of awakening conscience in regard to offering hospitality to others. The exhibition is hosted in the Parkinson Building, one of the heritage buildings of the University of Leeds, as part of the Brotherton Collections, curated by the University’s Libraries. Its rhizomatic story-telling of imaginaries of movement and homemaking reflects the overlapping biographies of its physical location: Leeds as a multicultural city with diverse migrant, exiled and diasporic communities, but also one of the foremost creative cities in the United Kingdom, and the University of Leeds as a pedagogical hub that hosts very diverse student populations from around the world.

Visual portrayals of fun in the sun in European news outlets misrepresent heatwave risks

AbstractThe ways in which news media communicate about heatwaves can influence how society conceptualises and addresses heatwave risks. We examined visual news coverage of the 2019 heatwaves in France, Germany, the Netherlands and the UK, using content and visual critical discourse analyses. Many visuals were positively valenced (in contrast to article texts), framing heatwaves as ‘fun in the sun’. The most prevalent type of images in all countries were photographs of people having fun in or by water. When images did depict the danger of heat extremes, people were largely absent. We conclude that this visual framing of heatwaves is problematic: first, by displacing concerns of vulnerability, it marginalises the experiences of those vulnerable to heatwaves; and second, it excludes opportunities for imagining a more resilient future. We conclude with suggestions to diversify the visual discourse on climate change and heatwaves in the news media.

Prettiness algorithms: Smartphones and the manipulation of taste

Often branded as ‘visual AI’, machine vision is the software technology that allows computers to see the world by interpreting images — used in social media platforms (identifying people in photographs), driverless cars (recognising pedestrians or road signs) and many more sinister applications. Researchers, journalists and activists have found that machine vision systems are biased in many of the same ways as the cultures that produced them. Starting from John Berger’s seminal Marxist analysis of how our culture informs the way we see, this article looks at some of the subtlest types of bias in machine vision systems: the automatic ‘enhancement’ of photos by smartphone cameras.

Voices of the Rainforest: A Day in the Life of Bosavi Papua New Guinea

Voices of the Rainforest: A Day in the Life of Bosavi Papua New Guinea

Review: The Mass Production of Memory: Travel and Personal Archiving in the Age of the Kodak, by Tammy S. Gordon

Review: <i>The Mass Production of Memory: Travel and Personal Archiving in the Age of the Kodak</i>, by Tammy S. Gordon

Criminal Detection through Face Recognition

Abstract: Face acknowledge is a champion among the most troublesome subjects in PC vision today. It has applications running from security and perception to delight destinations. Face affirmation writing computer programs are significant in banks, plane terminals, and various associations for screening customers.Germany and Australia have passed on face affirmation at edges and customs for Automatic Passport Control. Human face is a unique dissent having significant degree of change in its appearance which makes stand up to affirmation an irksome issue in PC vision. In this field, exactness and speed of ID is a guidelineissue. Various challenges exist for defy affirmation. The force of the system can be hindered by individuals who change their facial features through wearing shaded contact central focuses, growing a mustache, putting on genuine make-up, etc. Moral concerns are also related to the way toward recording, mulling over, and seeingcountenances. Various individuals dont support of perceptionstructures which take different photographs of people who have not endorsed this action. The goal of this paper is to surveydefy disclosure and affirmation methodology and offer an allout response for picture based face area and affirmation with higher precision, better response rate and a basic development for video perception. Game plan is proposed considering performed tests on various face rich data sets similar to subjects, position, sentiments and light. Index Terms: Face acknowledge, Security and perception, Automatic Passport Control,Malware detection, facial features, face rich data sets.

What do customers want? The impact of pricing tactic persuasion knowledge and frequency of exposure

PurposePrevious research has shown that consumers prefer a bonus pack to a price discount for virtue foods, whereas they prefer a price discount to a bonus pack for vice foods. Acting as a guilt-mitigating mechanism, a price discount justifies consumers' purchasing behavior, allowing them to save money and consume less vice foods. However, for virtue foods, neither the anticipated post-consumption guilt nor the resulting need for justification lead consumers to prefer a bonus pack to a price discount. This study investigates whether product promotions remain effective with other moderating variables.Design/methodology/approachThe authors use pricing tactic persuasion knowledge (PTPK), which refers to the consumer persuasion knowledge of marketers' pricing tactics, as a lens to understand whether the power of these promotions could be enhanced or mitigated. The authors inferred that increasing the frequency of exposure to these foods could positively influence consumers' purchasing choices. They conducted three studies to examine these effects. In Study 1, using pearl milk tea (vice food) and sugar-free tea (virtue food), the authors contended that consumers would prefer a price discount when purchasing pearl milk tea, but a bonus pack when purchasing sugar-free tea. In Studies 2 and 3, the authors varied the participants' frequency of exposure to photographs of people in everyday situations with vice (virtue) foods.FindingsIn Study 1, PTPK was shown to be more predictive of consumer choices regarding price discounts and bonus packs. In Studies 2 and 3, the authors contended that increased exposure to vice (virtue) foods increases the selection of vice (virtue) foods by participants who were unaware of having been exposed to vice (virtue) foods.Originality/valueThis research has not only made quite managerial and policy implications for marketing but also brought the theoretical contributions for marketing researches. This research demonstrates that either for vice foods or virtue foods, a price discount is preferred to a bonus pack.

A new context-based feature for classification of emotions in photographs

A high volume of images is shared on the public Internet each day. Many of these are photographs of people with facial expressions and actions displaying various emotions. In this work, we examine the problem of classifying broad categories of emotions based on such images, including Bullying, Mildly Aggressive, Very Aggressive, Unhappy, Disdain and Happy. This work proposes the Context-based Features for Classification of Emotions in Photographs (CFCEP). The proposed method first detects faces as a foreground component, and other information (non-face) as background components to extract context features. Next, for each foreground and background component, we explore the Hanman transform to study local variations in the components. The proposed method combines the Hanman transform (H) values of foreground and background components according to their merits, which results in two feature vectors. The two feature vectors are fused by deriving weights to generate one feature vector. Furthermore, the feature vector is fed to a CNN classifier for classification of images of different emotions uploaded on social media and public internet. Experimental results on our dataset of different emotion classes and the benchmark dataset show that the proposed method is effective in terms of average classification rate. It reports 91.7% for our 10-class dataset, 92.3% for 5 classes of standard dataset and 81.4% for FERPlus dataset. In addition, a comparative study with existing methods on the benchmark dataset of 5-classes, standard dataset of facial expression (FERPlus) and another dataset of 10-classes show that the proposed method is best in terms of scalability and robustness.

Analisis Penggambaran Gender Dalam Laporan Tahunan Pada Perusahaan Sektor Perkebunan Di Indonesia Tahun 2016-2018

This study proposes to provide analysis and understanding of gender representation in the annual report of plantation companies in Indonesia. The objects of this research are PT Austindo Nusantara Jaya, PT Dharma Satya Nusantara and PT Sinar Mas Agro Resources and Technology. This research uses descriptive qualitative with secondary data types obtained from the Annual Report of PT Austindo Nusantara Jaya, PT Dharma Satya Nusantara and PT Sinar Mas Agro Resources and Technology. Data collection is done by collecting techniques with photographs of people in the company's annual report. The analytical method used is content analysis. The steps of this research are: 1) evaluating photos of people in the annual report, 2) grouping photos by employees or non-employees, only men, only women, or men and women together, 3) an overview of the number of photos by group, 4) interpret research results found in annual reports. The results showed that gender depictions in the annual report of PT Austindo Nusantara Jaya, PT Dharma Satya Nusantara and PT Sinar Mas Agro Resources and Technology does not support equality between men and women. Photos of employees in the annual report are approved by male sex compared to women. Through analysis of sex photographs discussed in the annual report, it was found that sex was supportive in terms of role, place, clothing, and body language. But in the analysis of relative positions, men and women choose to stand or sit together

Eyetracking during picture naming predicts future vocabulary dropout in progressive anomia

ABSTRACT The dynamic and unpredictable nature of expressive vocabulary dropout in progressive anomia presents a challenge for language intervention. We evaluated whether eye gaze patterns during naming could predict anomia for the same items in the near future. We tracked naming accuracy and gaze patterns as patients with semantic (n = 7) or logopenic (n = 2) variants of Primary Progressive Aphasia or amnestic Alzheimer’s Disease (n = 1), named photographs of people and objects. Patients were tested three or more times spaced roughly evenly over an average duration of 19.1 months. Target words named accurately at baseline were retrospectively coded as either known (i.e., consistently named) or vulnerable (i.e., inaccurately or inconsistently named) based on naming accuracy over the study interval. We extracted gaze data corresponding to successful naming attempts and implemented logistic mixed effects models to determine whether common gaze measures could predict each word’s naming status as known or vulnerable. More visual fixations and greater visual fixation dispersion predicted later anomia. These findings suggest that eye tracking may yield a biomarker of the robustness of particular target words to future expressive vocabulary dropout. We discuss the potential utility of this finding for optimizing treatment for progressive anomia.

Documenting climate change

The impacts of climate change on people and societies are varied and nuanced, making it difficult to encapsulate in an image. Photographs of people can, however, create an emotional connection to what may otherwise be viewed as a natural problem.

Gendered Marketing of Food Supplements in Lifestyle Magazines in Greece

Background:Marketing of food supplements in Greece in print media has not been examined and this study is the first attempt to provide a comparative statistical analysis.Methods:Lifestyle magazines that were distributed all over Greece and aimed at women and men were collected in the years 2014 and 2016. Five criteria with their subcriteria were developed and were related to the branding of the food supplements; their quality characteristics; the information given about health concerns; photographs of people who promoted food supplements and to claims of their suitability.Results:It seems that in terms of product branding, women’s magazines were more likely to be targeted. Some quality characteristics such as information about the ingredients of food supplements or information about banned substances were more likely to be seen in women’s magazines in 2016. In 2014 and 2016, not all advertisements provided information about health concerns and among those which informed readers about health concerns, differentiation in target audiences was observed. Photographs that showed people promoting food supplements as well as claims of suitability for various categories of consumers, seem to be gendered in 2014 but this trend was not strong enough in 2016.Conclusion:It can be argued that the marketing of food supplements was aggressive and gendered in 2014 and changed in 2016 with better information on public health but had retained some gendered stereotypes.

Historic photographs of glaciers and glacial landforms from the Ralph Stockman Tarr collection at Cornell University

Abstract. Historic photographs are useful for documenting glacier, environmental, and landscape change, and we have digitized a collection of about 1949 images collected during an 1896 expedition to Greenland and trips to Alaska in 1905, 1906, 1909, and 1911, led by Ralph Stockman Tarr and his students at Cornell University. These images are openly available in the public domain through Cornell University Library (http://digital.library.cornell.edu/collections/tarr, last access: 15 March 2020; Tarr and Cornell University Library, 2014, https://doi.org/10.7298/X4M61H5R). The primary research targets of these expeditions were glaciers (there are about 990 photographs of at least 58 named glaciers), but there are also photographs of people, villages, and geomorphological features, including glacial features in the formally glaciated regions of New York state. Some of the glaciers featured in the photographs have retreated significantly in the last century or even completely vanished. The images document terminus positions and ice elevations for many of the glaciers and some glaciers have photographs from multiple viewpoints that may be suitable for ice volume estimation through photogrammetric methods. While some of these photographs have been used in publications in the early 20th century, most of the images are only now widely available for the first time. The digitized collection also includes about 300 lantern slides made from the expedition photographs and other related images and used in classes and public presentations for decades. The archive is searchable by a variety of terms including title, landform type, glacier name, location, and date. The images are of scientific interest for understanding glacier and ecological change; of public policy interest for documenting climate change; of historic and anthropological interest as local people, settlements, and gold-rush era paraphernalia are featured in the images; and of technological interest as the photographic techniques used were cutting edge for their time.

Nurses and Creative Writing: An Interview with Nurse Author Jeanne Bryner

Nurses and Creative Writing: An Interview with Nurse Author Jeanne Bryner

Human Emotion Identification Based on Facial Expression using Image Processing

The field of using image processing for automated human emotion identification based on facial expression is one that is rapidly growing and has many potential uses. There may be many advantages to understanding human emotions, such as better human-computer interaction and more accurate diagnosis of mental illness. Understanding emotions can help you communicate more effectively with others. Traditional methods of emotion recognition rely on human interpretation, which may be expensive, time-consuming, and prone to error. Recently though, advances in computer vision and machine learning have made it possible to design fully automated systems for identifying emotions based on facial expressions. These algorithms are competent in this area because of their analysis of facial expressions. This research provides a systematic review of previous work on emotion analysis from photographs of people's faces. Issues, boundaries, and potential directions for further study are all discussed. We also explore the many suggested methods for emotion recognition and provide a thorough evaluation of the existing datasets. The applications of AI-based emotion detection are also discussed, along with the need for objective standards of evaluation and verification of the results. Our research leads us to the conclusion that automated emotion recognition algorithms have great potential as a tool for enhancing human-computer interaction, mental health assessment, and other applications, but that more work needs to be done to improve their accuracy and robustness.