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The unique affordances and multimodality of the comics medium has been celebated in the literature of graphic medicine for its ability create innovative visal meaphors that help show unique and often difficult to express experiences of illness and disease. While acknowledging the importance and continuing relevance of that work, this article considers what effects might be created when those working in the comics medium decide that not showing a key aspect of the story world is a more compelling way to reveal the truth of the condition they wish to talk about. This form of storytelling, in which an important gap or absence is part of the diegesis, I refer to as 'elliptical testimony'. Considering three different strategies for creating meaning through absence I look at substituting in Spellbound by Bishakh Som, masking in I'm a Terminal Cancer Patient, but I'm Fine by Hilnama, and excluding in And Now I Spill the Family Secrets by Margaret Kimball. [ABSTRACT FROM AUTHOR]

In recent years, artificial intelligence (AI), especially deep learning models, has increasingly been integrated into diagnosing and treating diabetic retinopathy (DR). From delving into the singular realm of ocular fundus photography to the gradual development of proteomics and other molecular approaches, from machine learning (ML) to deep learning (DL), the journey has seen a transition from a binary diagnosis of "presence or absence" to the capability of discerning the progression and severity of DR based on images from various stages of the disease course. Since the FDA approval of IDx-DR in 2018, a plethora of AI models has mushroomed, gradually gaining recognition through a myriad of clinical trials and validations. AI has greatly improved early DR detection, and we're nearing the use of AI in telemedicine to tackle medical resource shortages and health inequities in various areas. This comprehensive review meticulously analyzes the literature and clinical trials of recent years, highlighting key AI models for DR diagnosis and treatment, including their theoretical bases, features, applicability, and addressing current challenges like bias, transparency, and ethics. It also presents a prospective outlook on the future development in this domain. [ABSTRACT FROM AUTHOR]

Wireless capsule endoscopy (WCE) has become an important tool for gastrointestinal examination due to its non-invasive nature and minimal patient discomfort. However, the quality of WCE images is often limited by built-in lighting and the complex gastrointestinal environment, particularly in the region filled with small intestinal villi. Additionally, the morphology of these villi usually serves as a crucial indicator for related diseases. To address this, we propose a novel method to enhance the clarity of small intestinal villi in WCE images. Our method uses a guided filter to separate the low- and high-frequency components of WCE images. Illumination gain factors are calculated from the low-frequency components, while gradient gain factors are derived from Laplacian convolutions on different regions. These factors enhance the high-frequency components, combined with the original image. This approach improves edge detail while suppressing noise and avoiding edge overshoot, providing clearer images for diagnosis. Experimental results show that our proposed method achieved a 45.47% increase in PSNR compared to classical enhancement algorithms, a 12.63% improvement in IRMLE relative to the original images, and a 31.84% reduction in NIQE with respect to the original images. [ABSTRACT FROM AUTHOR]

Dealing with disasters is typically illustrated with photos of the aftermath of disasters, notably collapsed infrastructure and destitute, hurt, or grieving people. Those images present the reality of disasters, but not the reality of actions seeking to avoid these scenes. This photo essay is of disaster risk reduction efforts as expressed through images. [ABSTRACT FROM AUTHOR]

Background/objectives: The way in which topics like suicide, mental health concerns and alcohol and other drug use are communicated matters. It has the potential to have either a positive or negative impact on people and communities, particularly those with a lived experience of these concerns. This article draws on the findings of a qualitative study designed to explore the experiences and perceptions of stakeholders on the imagery and language used to depict suicide, mental health concerns or alcohol and other drug use. Methods: The focus group method was used as a form of participatory action research to gain an in-depth understanding of the experiences and views of those who use or are impacted by language and imagery about suicide, mental ill-health and AOD use, including those with lived experiences of these topics. Results: A series of 10 focus groups were created in February and March 2022 with media and other professional communicators; people identifying as having a lived experience of suicide, mental ill-health or alcohol and other drug use; mental health and suicide prevention sector professionals; and people from priority populations (n = 49). From these focus groups, principles were developed as well as exemplars of helpful and less helpful depictions. Rather than prescriptive or static rules, the participants indicated that safe representations require an ongoing engagement with the principle of "do no harm". Conclusions: A positive conclusion arose—that words and images have the potential to promote help-seeking, challenge stigma or stereotypes and create change. [ABSTRACT FROM AUTHOR]

ardiovascular imaging has become the foundation of heart failure diagnostic studies. The most crucial technique for clinically diagnosing cardiac diseases is echocardiography. Depending on the positioning and angles of the probe, different cardiac views can be obtained during echocardiography. Therefore, the automatic classification of echo views, especially for computer systems and even automatic diagnosis in later stages, is the first step for echocardiogram diagnosis. In addition, the classification of heart views allows the tagging of echo videos to be done on a high scale and the possibility of database management and collection is provided. However, deep learning is an advanced machine learning method that is used to analyze both natural and medical images. But so far, it has not been widely used on cardiac ultrasound, the reason is the complexity of formats with multiple views and multi-view formats of echocardiogram. The proposed topic of this research is to provide novel and effective architectures for cardiac view classification. The aim of this study is to overcome the challenges in processing, categorizing and recognizing echo views stored as videos and images. In particular, in order to extract features, automatic methods and deep networks have replaced manual methods. In the presented solution, by using the transfer learning and the 3d-cnn method in image and video classification, we have improved the accuracy of echo views classification. [ABSTRACT FROM AUTHOR]

In traditional digital filing systems, people mostly use text as a key to categorise images, and retrieve them in the future. The use of other media as keys for image retrieval is rarely used, notwithstanding that multisensory digital media – mulsemedia – can be harnessed to improve users' performance and help them to retrieve their images. In this respect, olfactory media (engaging the sense of smell) is an example, as people can categorise their images by using congruent olfactory media. Accordingly, we investigated the impact of employing olfactory media as a key for retrieving a set of images. Moreover, we also studied the impact of the usage of olfactory media in this context on a user's performance and Quality of Experience (QoE). To this end, we developed an olfactory-enhanced application (SCENT2IMAGE) in which olfactory media was emitted alongside a 5X5 matrix of images, of which users had to recognize 4 images congruent with the emitted scents. Furthermore, we developed a word-only version of the application (WORD2IMAGE) in which words alone were used as an equivalent key instead of olfactory media. Forty-four participants were invited and took part in our experiment, evenly split into a control and experimental group. Results highlight that using olfactory media does have a significant impact on user performance by helping them find related images. Moreover, using olfactory effects in this context was also found to enhance user QoE. Lastly, our findings underscore that users were willing to use olfactory-enhanced applications for categorizing/retrieving their albums and images. [ABSTRACT FROM AUTHOR]

This study examines the evolving pedagogical role of images in French as a Foreign Language textbooks for upper primary levels in Algeria. It investigates their use in linguistic and communicative skills acquisition, cultural learning, and the diversification of visual strategies. The analysis of a textbook corpus aims to explore these aspects, highlighting the importance of visual aids in FFL teaching. [ABSTRACT FROM AUTHOR]

This article aims to study how historical documentaries handle the development of a tale. The initial premise is that documentaries are not a mere compilation and recounting of data but rather a narration constructed based on the perspective of the audiovisual language. To understand how filmmakers create the story, we studied documentary feature-length films on the Spanish Civil War between 2000 and 2014. The sequence has been taken as the unit of analysis, and a breakdown has been made of the types of images and sounds used according to duration, order, and predominance of plot or characters. The research bears on the concept of narrative strategy, which helps to understand the format's internal mechanism, considering three issues: the production approach, the visual solution, and the narrative decision. The study of the selected corpus detected eleven narrative strategies-eleven ways to portray the same event from the past, with different purposes and intentions. [ABSTRACT FROM AUTHOR]

The Ming Dynasty was the most popular and prosperous period in the culture of scarves in ancient Chinese society. During this period the types of scarves evolved and alienated in a large number and there were diverse presentations in terms of structure shape and expression. The wearing groups also included almost all social classes of men among whom the scholar group was the most prominent. The popular fashion of this kind of scarf also makes the Ming Dynasty retain more historical materials related to scarvs and Ru Shui Jin Pu is an rare ancient book that integrates the clear drawing and text annotation of the Ming Dynasty' s scarvs. The book is divided into four parts inscription catalogue map and postscript. In the part of the map 32 types of clothes in the Ming Dynasty are clearly drawn. The large number and variety are important historical materials for studying the fashion of the Ming Dynasty' s scarvs and also contribute to the study of the culture of headdress in the Ming Dynasty. Based on this this paper first combed the texts and images contained in Ru Shui Jin Pu and then used the literature research method to study the background of the book and the related text annotations and extended contents of the scarves. Secondly it summarized the structure and modeling characteristics expression methods and decorative techniques of the scarves by combining the mutual proof method with the comparative analysis method. Finally it analyzed the era mapping and objective limitations of the popular fashion of scarves in the Ming Dynasty presented by Ru Shui Jin Pu by the art archaeology method. The research shows that Ru Shui Jin Pu was written by Zhu Shuxun a son of the imperial clan during the Chongzhen period of the late Ming Dynasty. The 32 types of scarvs in the book are either inherited from the predecessors or designed by the wearers. As for the first 13 types of scarves the source purpose wearers and shape description of the scarves are recorded in detail. As for the latter 19 types of scarves the book mainly describes the metophor material selection and production techniques of the scarves. The scarves are divided into four types in terms of basic structure front and back drape ones front drape ones back drape ones and zero drape ones. The scarves are divided into four types in terms of shape flat-top ones square-top ones arc-top ones and dome ones. The scarves are divided into four types in terms of expression of the creation quasi-physical ones quasiword ones associative ones and other others. The decorative techniques used are rich and varied such as changing the shape of the scarves with concrete or abstract shapes or decorating them with painting pasting embroidery and other methods. The change of the shape reflects the evolution of the popular fashion of scarves in different periods. The integration of the scarves compiled by Ru Shui Jin Pu intergrates the styles of the early and late Ming Dynasty reflecting the two aesthetic styles of retro and novelty and recording the aesthetic characteristics of the times behind the popular performance of the scarves in the Ming Dynasty. The compilation thought embodies the author' s admiration for the previous generation of celebrities and the yearning for gentleman's character. At the same time combined with the creation background and compilation content of this book we can also see the aesthetic fashion mapping of the times in the scarves of the literati in the late Ming Dynasty under the disorder of social hierarchy such as the pursuit of retro the pursuit of fantastic and the worship of immortality as well as the limitations of the volume and information accuracy of the scarves caused by subjective choice and objective vision. [ABSTRACT FROM AUTHOR]

During national crises, political elites often rally around the flag, promoting a central message to restore unity and calm the public. COVID-19 provided such a crisis. But did elites rally? The pandemic occurred at a point of extreme polarization in the United States, which threatens the potential for a rally. In this article, we argue that messaging about masking during COVID-19 offers an opportunity to test the comparative effects of a rally versus polarization. To do so, we use a unique measure: visual public communication by members of Congress (MOCs). We extract 340,000 images from congressional Twitter and Facebook accounts and employ supervised machine-learning methods to identify when MOCs posted images of people wearing masks. We find evidence of both rally effects and polarization. Trump's actions are especially important: while Trump-loyal Republicans are less likely to post masks, all Republicans increased posting masks after Trump first appeared wearing a face mask. [ABSTRACT FROM AUTHOR]

Copyright of National Palace Museum Research Quarterly is the property of National Palace Museum and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Tidsskrift for Psykisk Helsearbeid is the property of H. Aschehoug & Co. (W. Nygaard) AS and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This article explores how universities construe organizational identities and engage digital audiences through images on web homepages. Combining visual content analysis and a discourse-analytic approach informed by social semiotics, I interpret the discourses of identity in 400 images from organizational homepages of four top-tier public universities in Sydney, Australia – University of Sydney, University of New South Wales, University of Technology Sydney, and Macquarie University. Based on the social semiotic interpretation of images, I identify eight identity icons, each deploying a combination of semiotic resources to represent a specific organizational identity. The analysis suggests that universities prioritize featuring people, which results in an augmented sense of social presence on the homepage. Lastly, four identified strategies for digital audience engagement in images – proximation, alignment, equalization, and subjectivation – point to how these are instrumental in representing university life as both individual and shared experiences. [ABSTRACT FROM AUTHOR]

Objective: To investigate the consistency of Chatbot Generative Pretrained Transformer (ChatGPT)‐4 in the analysis of clinical pictures of common laryngological conditions. Study Design: Prospective uncontrolled study. Setting: Multicenter study. Methods: Patient history and clinical videolaryngostroboscopic images were presented to ChatGPT‐4 for differential diagnoses, management, and treatment(s). ChatGPT‐4 responses were assessed by 3 blinded laryngologists with the artificial intelligence performance instrument (AIPI). The complexity of cases and the consistency between practitioners and ChatGPT‐4 for interpreting clinical images were evaluated with a 5‐point Likert Scale. The intraclass correlation coefficient (ICC) was used to measure the strength of interrater agreement. Results: Forty patients with a mean complexity score of 2.60 ± 1.15. were included. The mean consistency score for ChatGPT‐4 image interpretation was 2.46 ± 1.42. ChatGPT‐4 perfectly analyzed the clinical images in 6 cases (15%; 5/5), while the consistency between GPT‐4 and judges was high in 5 cases (12.5%; 4/5). Judges reported an ICC of 0.965 for the consistency score (P =.001). ChatGPT‐4 erroneously documented vocal fold irregularity (mass or lesion), glottic insufficiency, and vocal cord paralysis in 21 (52.5%), 2 (0.05%), and 5 (12.5%) cases, respectively. ChatGPT‐4 and practitioners indicated 153 and 63 additional examinations, respectively (P =.001). The ChatGPT‐4 primary diagnosis was correct in 20.0% to 25.0% of cases. The clinical image consistency score was significantly associated with the AIPI score (rs = 0.830; P =.001). Conclusion: The ChatGPT‐4 is more efficient in primary diagnosis, rather than in the image analysis, selecting the most adequate additional examinations and treatments. [ABSTRACT FROM AUTHOR]

The article analyses expedition sketches of professional artist Lyudmila Mikhailovna Pozdeeva from the collections of the National Museum of the Republic of Tatarstan and the “Miraskhane” Written Heritage Center of G. Ibragimov Institute of Language, Literature and Art of the Republic of Tatarstan Academy of Sciences, which were made by the master during the expeditions of 1926 and 1927 under the leadership of N. I. Vorobyev. Costume complexes of Tatars of different subethnic and ethnographic groups are analysed. Particular attention is paid to the scientific component of L. M. Pozdeeva’s work, the consistency of the sketches to written sources, museum materials and expedition photographs. The author of the article identified nine watercolours and one graphite pencil sketch, which depict the clothes of men and women of different ages. The pieces were made in the Chelny, Chistopol, Sviyazhsk, and Tetyush cantons, in settlements such as Nizhneye Bishevo, Kainly, Akbulatovo, Stary Tatarsky Adam, Molkeevo, Stary Kurbash, and Bakorchi (Bakrchi). Some images are duplicated by photographs, which became the visual accompaniment to the texts of N.I. Vorobyev’s academic publications. The sketches by L.M. Pozdeeva found by the author of the article fully correspond to the photographic images, which is evidence of the precise reproduction of what she saw during the expeditions. The artist chose different angles of the characters in national clothing, thereby creating not just an ethnographic copy, but an artistic image.

If images were once conceived either as subordination or oppositions of words, the advent of the Internet has started new relationship dynamics between them. Within this digital scenario, vision and textuality intensely intertwine in the form of captions, posts, hyperlinks or other kind of social media content, daily handled by users. In this context, autobiographical narratives will take on a major role, shaping the way in which the subject conceives, forges and registers his or her identity in relation to the reader/viewer. This article aims to address the question, more present than ever, of how certain autobiographical narratives are disseminated through social networks, and how image and narrative dialogue within this framework. By addressing specific cases found on platforms such as Instagram, we will try to elucidate how these publications point to an ambivalent relationship with visual tropes or narratives associated with certain life experiences, either questioning it or contributing to the creation of a collective narrative. A complex interplay of image and narrative that will affect not only how we share life, but also how we understand it and construct it together with others in a changing world.

This article looked at how the ‘Ghanaian Times’ newspaper, using stories sourced from the British Broadcasting Corporation (BBC), framed Africa to the rest of the world. The study which utilized the mixed approach also employed the gatekeeping, framing and cultural imperialist theories in its attempt to find out which of the regional blocs in Africa dominated the coverage and whether the portrayal was positive or negative. The study found that the majority of the stories that the ‘Ghanaian Times’ sourced from the BBC were negative about Africa hence framing Africa as an unhealthy place for living. Out of the 154 stories the newspaper sourced from the BBC, only 52 stories focused on the positive happenings in Africa while 94 stories painted a catastrophic image about Africa. Also, political unrest and crime were the two dominant themes Africa was associated with. In all, the general image of Africa as portrayed by the newspaper was negative as the editors focused more on negative stories of Africa compared to the positives amidst the abundance of stories published by the BBC. This arguably means that Africa’s negative image could only be corrected if editors are deliberate in selecting more positive stories about Africa for publication. This work will indeed add to the literature on the framing of Africa in the media especially the contribution of the African media to the dominant negative image Africa continues to be associated with.

In the present situation human health is a very important factor. With today's growing technology, health conditions are deteriorating day by day. Malnutrition, lifestyle play a very important role. These are leading to many diseases such as respiratory infections, heart disease, diabetes, Cancer, Alzheimer's, strokes and many more. Among these, few diseases are curable, due to the facilities available. Whereas few may be non-curable if care is not taken in the initial stages. Cancer poses the biggest threat among all life-threatening diseases. An efficient lesion segmentation method is introduced for the detection of Melanoma skin cancer disease at the preliminary stages using Adaptive Contour Model (ACM). High-quality segmentation is achieved based on contour features and sharp edge detection using ACM. The performance of the proposed Adaptive Contour Model (ACM) is tested upon PH2 and ISIC Challenge 2017 Dataset. The Performance matrices for the segmentation process are measured in terms of Jaccard index (JA), Dice coefficient (DI) and accuracy that are found to be 79.23, 87.26 and 94.63 considering ISIC dataset and 89.14, 93.98 and 96.95 which is quite high considering PH2 dataset. A method for detection of melanoma has been the critical need of the day. The proposed method shows that the performance of the Adaptive Contour Model (ACM) is more than 95%, which is better than other methods. [ABSTRACT FROM AUTHOR]

In Human Nature, Hobbes argues for what I call the ‘Great Deception Thesis': “whatsoever accidents or qualities our senses make us think there be in the world, they are not there, but are seemings and apparitions only”. I argue that both the thesis and Hobbes’ arguments for it have been misunderstood. Rather than arguing for indirect realism or a primary/secondary quality distinction, Hobbes claims that no sensory experience resembles its object. I conclude by showing how Hobbes can account for the usefulness of images even in the absence of any resemblance between those images and the objects that cause them. If I am right, Hobbes presents a distinctive and intriguing theory of perception, one that emphasizes the dynamic nature of experience. [ABSTRACT FROM AUTHOR]

Brain tumor (BT) is an awful disease and one of the foremost causes of death in human beings. BT develops mainly in 2 stages and varies by volume, form, and structure, and can be cured with special clinical procedures such as chemotherapy, radiotherapy, and surgical mediation. With revolutionary advancements in radiomics and research in medical imaging in the past few years, computer-aided diagnostic systems (CAD), especially deep learning, have played a key role in the automatic detection and diagnosing of various diseases and significantly provided accurate decision support systems for medical clinicians. Thus, convolution neural network (CNN) is a commonly utilized methodology developed for detecting various diseases from medical images because it is capable of extracting distinct features from an image under investigation. In this study, a deep learning approach is utilized to extricate distinct features from brain images in order to detect BT. Hence, CNN from scratch and transfer learning models (VGG-16, VGG-19, and LeNet-5) are developed and tested on brain images to build an intelligent decision support system for detecting BT. Since deep learning models require large volumes of data, data augmentation is used to populate the existing dataset synthetically in order to utilize the best fit detecting models. Hyperparameter tuning was conducted to set the optimum parameters for training the models. The achieved results show that VGG models outperformed others with an accuracy rate of 99.24%, average precision of 99%, average recall of 99%, average specificity of 99%, and average f 1-score of 99% each. The results of the proposed models compared to the other state-of-the-art models in the literature show better performance of the proposed models in terms of accuracy, sensitivity, specificity, and f 1-score. Moreover, comparative analysis shows that the proposed models are reliable in that they can be used for detecting BT as well as helping medical practitioners to diagnose BT. [ABSTRACT FROM AUTHOR]

The diagnosis of hysteria, despite being fundamental in the birth of psychiatry, has currently been removed from nosography. This choice speaks of the renunciation by contemporary nosography of understanding psychopathological conditions as structural entities, with internal coherence and meaningfulness – which on the contrary should be reconsidered. Hysteria represents a mirror of social and cultural changes. The metamorphoses throughout history of hysterical symptoms reflect the changing interests of medicine (the greater legitimation of somatic symptoms over psychic ones) and, in general, mirror the increasing importance of images in the contemporary world. Despite its nosographical fragmentation, hysteria continues to be talked about. Phenomenologically, hysteria is described not as a diagnosis but as an existential position, freeing it from gender prejudices. Hysterical persons suffer from a hypo-sufficiency of the self, from a difficulty in feeling from within, which ends up hypertrophying the identity definitions coming from without: the gaze of others, socio-cultural stereotypes, gender models. Visibility therefore takes on a central role, and images become a vehicle to represent oneself – capable of attracting the attention of others and enchanting them. Different powers have been attributed to images throughout the history of thought: that of paralyzing, that of moving to action, that of underlining the contingency of experience. Hysterical persons embody images, generating with their symptoms a world of representations. However, what characterizes hysteria is not the symptom, but the use made of that symptom: it becomes a catalyst for the gaze of others, which allows one to assume an otherwise lacking identity-consistency. For this reason, hysterical persons are not only passively subject to their symptoms, but actively make use of them in interpersonal relations. [ABSTRACT FROM AUTHOR]

It is commonly assumed that images, whether in the world or in the head, do not have a privileged analysis into constituent parts. They are thought to lack the sort of syntactic structure necessary for representing complex contents and entering into sophisticated patterns of inference. I reject this assumption. "Image grammars" are models in computer vision that articulate systematic principles governing the form and content of images. These models are empirically credible and can be construed as literal grammars for images. Images can have rich syntactic structure, though of a markedly different form than sentences in language. [ABSTRACT FROM AUTHOR]

In this article, I explore the use, production, and readings of images in antiracist work as processes in constant tension with racist logics. Racist logics are deceptive and entrapping, and the visible world is a particularly dynamic arena in which to analyse this. Images, specifically photographs, incorporate a nuanced and productive contradiction between their ability to illustrate, explain and evoke, on the one hand, while also ensnaring, on the other, partly through alluring and providing pleasure. This contradiction means that anti-racist projects may include the possibility of re-inscribing racist discourse and practice. Drawing on empirical examples from Mexico, this article interrogates how photographic representations of Blackness have been entangled with the racist logics and racial projects that feed them. Racialised images that emphasise the physical body of Black people raise questions about how mestizaje, Latin America's main racial formation, has coded the visual space of representation in confusing ways. [ABSTRACT FROM AUTHOR]

The paper presents findings from a study that examined, through the lens of the Image Having layer of the Pirie–Kieren model, the qualitative characteristics of the images that different children formed when engaging with eight, novel partitive quotient tasks. The Image Having layer is the first point of abstraction within the Pirie–Kieren model. Therefore, this research is significant in aiming to advance theoretical insight into how the notion of child-created images relates to the development of children's mathematical understanding, in the context of novel for them tasks. This study adopted a qualitative, microgenetic research design and involved nine Year 5 (aged 9–10 years) children. Data based on children's verbal responses and jottings were collected through multiple trials over eight individual sessions with each child. Analysis of 72 interview transcripts showed that children formed and used a range of different images that varied across tasks but also within the same task. This study provides a nuanced description of qualitative distinctions in the nature of child-created images. It thus reveals varied dimensions of a dynamic process of knowledge development and sense-making. This highlights, for educators, the need to be aware of and adaptive to the varied and dynamic dimensions of knowledge that children draw from, when dealing with novel tasks, and which change as children's understanding of new mathematical content develops. [ABSTRACT FROM AUTHOR]

Corrosion negatively impacts the functionality of civil structures. This paper introduces a new methodology that combines the fractality of vibration signals with a data processing stage utilizing autoencoders to detect corrosion damage in a truss-type bridge. Firstly, the acquired vibration signals are analyzed using six fractal dimension (FD) algorithms (Katz, Higuchi, Petrosian, Sevcik, Castiglioni, and Box dimension). The obtained FD values are then used to generate a gray-scale image. Then, autoencoders analyze these images to generate a damage indicator based on the reconstruction error between input and output images. These indicators estimate the damage probability in specific locations within the structure. The methodology was tested on a truss-type bridge model placed at the Vibrations Laboratory from the Autonomous University of Queretaro, Mexico, where three damage corrosion levels were evaluated, namely incipient, moderate, and severe, as well as healthy conditions. The results demonstrate that the proposal is a reliable tool to evaluate the condition of truss-type bridges, achieving an accuracy of 99.8% in detecting various levels of corrosion, including incipient stages, within the elements of truss-type structures regardless of their location. [ABSTRACT FROM AUTHOR]

In approximation theory, classical discrete operators, like generalized sampling, Szász‐Mirak'jan, Baskakov, and Bernstein operators, have been extensively studied for scalar functions. In this paper, we look at the approximation of curves by a class of discrete operators, and we exhibit graphical examples concerning several cases. The topic has useful implications about the computer graphics and the image processing: We discuss applications on the approximation and the reconstruction of curves in images. [ABSTRACT FROM AUTHOR]

Increased urbanization coupled with climate change is increasing the number and intensity of stormwater flooding events. Implementing efforts to successfully manage stormwater flooding depends on understanding how people perceive these events. While images of stormwater flooding abound, how these images influence perceptions about flooding events or management options remains understudied. Our objective is to contribute to the general understanding of how various types of images depicting stormwater runoff and stormwater related flooding influence individual and group interpretations of causes of events, major impacts of those events, and responsibility for managing stormwater related events. To this end, we convened focus groups, gave participants numerous photos of stormwater flooding, asked them to identify which images were most concerning, and to then discuss the specific aspects of the photos that prompted concern. We also tested whether a priming image implicating climate change or development as a cause of stormwater flooding influenced viewer reactions. Finally, we asked participants about preferences for who should manage stormwater. Our results revealed that photo location, the water's appearance, and what people were doing in the photo influenced levels of concern. We also found that priming seems to affect opinions regarding urban stormwater management. Finally, there is some evidence that the absence of people in the photo may affect beliefs about who should manage stormwater. [ABSTRACT FROM AUTHOR]

Copyright of Cuadernos del Centro de Estudios de Diseño y Comunicación is the property of Cuadernos del Centro de Estudios de Diseno y Comunicacion and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The conservation of biodiversity in the tropics has prompted the need for extended and accurate forest inventories in mountainous landscapes, where satellite imagery and radiative transfer modeling of forests have acquired much relevance. Last-generation classification algorithms (i.e. machine learning) using terrain information have proven useful for mapping forest types, however, the accuracy of classifications is measured on average over a large extent, and little emphasis has been placed on predicting which illumination configurations could in fact cause high uncertainty in the classification results. This paper presents a 3D modeling approach adapted to the Discrete Anisotropic Radiative Transfer (DART) image simulator, which indicates whether forest types are distinguishable in a set of steep terrain configurations. The approach also describes a comparison of simulated and real forest scenes on slopes at high (4 m) spatial resolution. This method was applied to estimate the spectral separability of three forest types (oak, pine, and high tropical forests) on steep terrain in Mexico. For extreme (low or high) solar incidence angles, the pine and high tropical forests were indistinguishable, and by contrast, they were distinguishable on slopes near to the solar perpendicular plane. As a consequence, to maximize favourable slope configurations, we recommend to incorporate images acquired in the morning and in the afternoon for machine learning classification algorithms. [ABSTRACT FROM AUTHOR]

The role that visual discriminative ability plays among giant pandas in social communication and individual discrimination has received less attention than olfactory and auditory modalities. Here, we used an eye-tracker technology to investigate pupil fixation patterns for 8 captive male giant pandas Ailuropoda melanoleuca. We paired images (N =  26) of conspecifics against: 1) sympatric predators (gray wolves and tigers), and non-threatening sympatric species (golden pheasant, golden snub-nosed monkey, takin, and red panda), 2) conspecifics with atypical fur coloration (albino and brown), and 3) zookeepers/non-zookeepers wearing either work uniform or plain clothing. For each session, we tracked the panda's pupil movements and measured pupil first fixation point (FFP), fixation latency, total fixation count (TFC), and duration (TFD) of attention to each image. Overall, pandas exhibited similar attention (FFPs and TFCs) to images of predators and non-threatening sympatric species. Images of golden pheasant, snub-nosed monkey, and tiger received less attention (TFD) than images of conspecifics, whereas images of takin and red panda received more attention, suggesting a greater alertness to habitat or food competitors than to potential predators. Pandas' TFCs were greater for images of black-white conspecifics than for albino or brown phenotypes, implying that familiar color elicited more interest. Pandas reacted differently to images of men versus women. For images of women only, pandas gave more attention (TFC) to familiar combinations (uniformed zookeepers and plain-clothed non-zookeepers), consistent with the familiarity hypothesis. That pandas can use visual perception to discriminate intra-specifically and inter-specifically, including details of human appearance, has applications for panda conservation and captive husbandry. [ABSTRACT FROM AUTHOR]

Sustainability reporting has been established as a dominant but problematic communication practice in global sustainability management. In this paper, we challenge the commonplace view of reporting as the simple and textual transmission of information, by interpreting corporate sustainability reports as visual artefacts that encourage particular views of environmental issues. We discuss visualization as a key practice in communication and rhetoric, asking what visual managerialism looks like in corporate reports, focusing on a corpus drawn from the Swedish United Nations Global Compact. We engage in a three-stage rhetorical critique to identify three kinds of visualizations: numerical, diagrammatic, and pictorial, establishing how they emphasize communicative characteristics such as logic, simplicity, and clarity. We consolidate these characteristics with the term 'Powerpoint Imagination,' arguing that they construct environmental problems in terms of a technocratic solutionism, i.e., efficiency, standardization and control. We discuss some issues with the Powerpoint Imagination by contrasting it with other images from sustainability reports, concluding with implications for future research. [ABSTRACT FROM AUTHOR]

A novel approach that combines segmented fundus images (FIs) and optical coherence tomography image (OCTIs) are presented here, by incorporating deep learning network (DLN) techniques, to address the imperative need for advanced diagnostic algorithms in detecting and classifying glaucoma. By combining these two images, glaucoma diagnoses are made to improve the accuracy with more reliability. Multi modal convolutional neural networks (MMCNNs) are proposed for automatically extracting discriminatory features from both segmented FIs and OCTIs, allowing for comprehensive ocular analysis. A significant improvement in glaucoma diagnosis is achieved through segmentation of both FIs and OCTIs, ensuring robustness generalization to diverse clinical scenarios, DLN models are trained on datasets encompassing a wide range of glaucoma cases. The integrated approach outperforms individual modalities in terms of early detection of glaucoma and accurate classification. This method demonstrates promising potential in early glaucoma detection due to its effectiveness. By combining segmented features from both FIs and OCTIs through MMCNNs, improved efficiency in diagnosing predominant ocular glaucoma disorder is achieved compared to existing methods. Within the scope of this research, GoogLeNet (GN) is applied to independently classify glaucoma (uni-modal) in segmented FIs and OCTIs, providing a basis for comparison with the evaluation of MMCNNs. [ABSTRACT FROM AUTHOR]

English as a Foreign Language (EFL) textbook image resources provide important materials and ways of learning for EFL students. Previous studies on the meaning and function of images in Chinese EFL textbooks tend to take pedagogy and cognitive psychology as main perspectives. Based on visual grammar, this article analyzes the image resources in Chinese junior high school EFL textbooks from a multimodal perspective, attempting to explore how the images realize three meta-meanings. It is found that cartoon, photo, table, and diagram are four main types of images in Yilin EFL textbooks. Quantitative analysis and qualitative analysis show that the images in the textbooks realized the representational meaning, interactive meaning and compositional meaning, but there are still some problems in image design, such as insufficient image types, lack of images promoting knowledge comprehension, and inadequate realization of compositional meaning of images. The research results offer some implications for Chinese EFL textbook editors to design textbooks, and also provide some suggestions for Chinese EFL teachers' teaching practice and students' learning. [ABSTRACT FROM AUTHOR]

Images are today at the centre of multiple social and technological tensions as a consequence of the adoption of digital coding, of the massive diffusion of social networks and of the algorithmic processing to which they are subject, resulting in new opportunities for developing analytical inquiries and meaning-producing social actions. In this introduction, the authors intend to reconstruct the broad context that makes images one of the most important resources of the digital era and to focus on some of the research tracks that characterize it. In the first part, they begin by focusing on the relationship between images and the digital, which they retrace in accordance with the selection of three key moments: the transition from ontology to the epistemology of digital media; the opening, by social networks and portable devices, of a field for the computational study of contemporary cultures; and, finally, the analytical potential arising from the encounter between digital archives and computer algorithms. In the second part, they present the three axes around which this issue is structured: archives, identity and algorithms. They first of all discuss the concept of the archive, by presenting four different understandings it has come to bear in conjunction with digital encoding – the archive as heritage, resource, effect and as database. They go on to address the relation between images and identities, arguing that social platforms and visual apps are a new domain for identity experimentation and social aggregation. Finally, they discuss the issue of algorithms and more generally of the new computational economy that associates large amounts of data with their mobilization as operational images. [ABSTRACT FROM AUTHOR]

AbstractDespite increasing attention to images in the study of world politics, the role of visual representations in transnational governance processes in general and migration governance, in particular, has received less attention. This paper aims to fill this gap by examining the visual representation of migration governance by the two Canadian government institutions responsible for it: Immigration, Refugees and Citizenship Canada (IRCC) and the Canada Border Services Agency (CBSA). Through a multi-modal analysis of their X (formerly Twitter) images, the paper shows how they tend to shy away from a visual representation of people on the move, privileging a technical communication in an aspiration toward a “neutral” representation of migration issues. Secondly, it sheds light on the discrepancies between the policies directed toward Afghani and Ukrainian refugees and the unexpectedly undifferentiated visual communication about the two groups. Finally, the paper explores what the pictures accompanying X (formerly Twitter) posts of IRCC and CBSA can tell about how these government institutions represent themselves. Findings showed that government institutions’ esthetic practices are not always in line with the institutional migration policies and text narratives, suggesting that different government implementation tools (i.e., regulations, practices, textual discourses) may not reinforce each other but advance alternative perspectives. [ABSTRACT FROM AUTHOR]

Research on political conflict often overlooks the role of visual-based platforms like Instagram in expressing political discontent, focusing primarily on textual content from newspapers and social media. This paper examines the practicalities and challenges of conducting visual research on Instagram, particularly in the context of comparative studies. We highlight the difficulties associated with sampling representative visual content. Through a small case study, we illustrate how hashtags associated with a single country can generate multiple conflicts, using indicators developed in political protest research and contentious politics. The existence of diverse debates within and across hashtags complicates cross-country comparisons of Instagram content and conflict dynamics. To address this issue, we propose an analytical tool for cross-hashtag analysis, allowing for the assessment of degrees of conflict. [ABSTRACT FROM AUTHOR]

This article uses critical discourse analysis to investigate artificial intelligence (AI) generated images of aged care nurses and considers how perspectives and perceptions impact upon the recruitment and retention of nurses. The article demonstrates a recontextualization of aged care nursing, giving rise to hidden ideologies including harmful stereotypes which allow for discrimination and exploitation. It is argued that this may imply that nurses require fewer clinical skills in aged care, diminishing the value of working in this area. AI relies on existing data sets, and thus represent existing stereotypes and biases. The discourse analysis has highlighted key issues which may further impact upon nursing recruitment and retention, and advocates for stronger ethical consideration, including the use of experts in data validation, for the way that aged care services and nurses are depicted and thus valued. [ABSTRACT FROM AUTHOR]

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Reminiscing about childhood in the city is often associated with memories of places, spaces and games. In this article I will look at childhood in the context of games in the city and its neighborhoods, spaces and quarters. I use anthropological, historical and visual approaches to look at the way children use these spaces to play games. The purpose is to show the connection between places and the so-called „ownership of territories“ as part of creating images of childhood. The focus will be on places for play and neighborhoods as spaces of interaction and sense of belonging. Through the analysis of stories and visual data related to the city of Plovdiv, games and images of childhood from different periods of time will be presented. [ABSTRACT FROM AUTHOR]

This article elaborates on opportunities and challenges related to implementing critical visual literacy (CVL) in English as a foreign language (EFL) classrooms in Norwegian secondary schools as an approach to preparing learners to face the complexity and diversity of today's textual landscapes. The study draws on a doctoral research project which focused on the meaning-making processes learners engage in when discussing images from the perspective of intercultural learning and expands on this by giving voice to the participating students and teachers. Data consisted of researcher field notes and learner responses from a 16-week intervention in which 83 upper secondary EFL learners in Norway were introduced to CVL practices as an integrated part of their EFL classes. Using thematic analysis, the data was analysed with a focus on the opportunities and challenges that arose from teachers and learners enacting CVL in the EFL classroom. Three themes were identified and discussed, including 'Changing classroom practices', 'Co-construction processes' and 'Reading and talking about images'. [ABSTRACT FROM AUTHOR]

Ischemic brain strokes are severe medical conditions that occur due to blockages in the brain's blood flow, often caused by blood clots or artery blockages. Early detection is crucial for effective treatment. This study aims to improve the detection and classification of ischemic brain strokes in clinical settings by introducing a new approach that integrates the stroke precision enhancement, ensemble deep learning, and intelligent lesion detection and segmentation models. The proposed hybrid model was trained and tested using a dataset of 10,000 computed tomography scans. A 25-fold cross-validation technique was employed, while the model's performance was evaluated using accuracy, precision, recall, and F1 score. The findings indicate significant improvements in accuracy for different stages of stroke images when enhanced using the SPEM model with contrast-limited adaptive histogram equalization set to 4. Specifically, accuracy showed significant improvement (from 0.876 to 0.933) for hyper-acute stroke images; from 0.881 to 0.948 for acute stroke images, from 0.927 to 0.974 for sub-acute stroke images, and from 0.928 to 0.982 for chronic stroke images. Thus, the study shows significant promise for the detection and classification of ischemic brain strokes. Further research is needed to validate its performance on larger datasets and enhance its integration into clinical settings. [ABSTRACT FROM AUTHOR]

With the proliferation of the use of the Internet and social media, the digital media industry has grown enormously in recent years. However, this has brought some challenges, including issues of content security and copyright violation. In this paper, we propose a fusion-based secure watermarking algorithm that we have named "FuSIW". This uses a hashing scheme, to guarantee copyright protection and authentication of RGB images. The algorithm uses the non-subsampled contourlet transform (NSCT) to create a fused watermark image. This contourlet transform (CT) and randomised-singular-value-decomposition (RSVD) based approach allows concealment of the encrypted fused watermark image in the blue channel of the cover image. Subsequently, the hash value of the cover image is inserted into the green channels of the host image. Experimental evaluation indicates that the FuSIW algorithm provides security from geometric attacks and several other common forms of attack. Simulations indicate that the proposed system exhibits improved robustness and security compared to existing methods. [ABSTRACT FROM AUTHOR]

In this piece I reflect on Christoforos Bouzanis' book, Social Imaginary and the Metaphysical Discourse , discussing its main contribution to the issue of social science's relation to philosophy and examining Bouzanis' concept of social imaginary as an imagery, raising questions of sense. [ABSTRACT FROM AUTHOR]

The fish are incorporated with ice to preserve their freshness when sold on the market. Ordinary people can only detect its freshness with some basic freshness knowledge. Therefore, non-destructive fish freshness inspection is an innovative solution to help. This dataset provides a medium to develop a system for non-destructive detection of fish freshness. There are three data variations: sensor data, images, and organoleptic examination. This dataset includes three fish species: mackerel, tilapia, and tuna, using 21 fish of each species. Data generation was carried out for 11 days, where 800 MQ (Metal Oxide) 135 and TGS (Taguchi Gas Sensor) 2602 sensor data and 80 images were generated every day. Organoleptic examinations were carried out using the Indonesian National Standard (SNI) 2729-2013 on six parameters: eyes, gills, body surface mucus, meat, smell, and body textures. This dataset can be used to develop a fish freshness detection system, regression modeling to estimate the deterioration in fish freshness, and standard grouping of freshness classes.

ABSTRACTImpacts of the surrounding land use land cover changes on Suba Sabeta Forest over the past three decades from 1990 to 2020 and associated community perception were assessed employing an integrated approach of Landsat images analysis, household survey, key informants interview and focus group discussion. The study involved collection of both quantitative and qualitative data which were analyzed using descriptive statistics. The results revealed that forests and shrub declined from 9,220 ha and 1335 ha to 2702 ha and 783 ha while settlement and bare land increased from 866 ha and 273 ha to 5,589 ha and 3,978 ha, respectively. Cultivated land increased from 12,162 ha in 1990 to 14,329 ha in 2005 and then declined to 10,811 ha by 2020. Respondents’ responses also indicated a drastic decline in the forest cover related to fuel wood collection (81.6%), settlement (13.8%), cutting trees for construction (3.3%) and expansion of cultivated land (1.3%). According to the respondents poverty (79.08%) and population growth (20.92%) were the underlying causes of the forest cover decline. Responses further revealed disappearance of indigenous plants (biodiversity loss) (73.2%), soil erosion (18%) and decline in agricultural production (8.8%) related to the decline in forest cover. Thus, protection of the remnant forest, reforestation and developing renewable alternative energy sources might help to mitigate further decline in Suba Sebeta Forest cover and associated impacts.

This article analyses the semantics of εἴδωλον, εἰκών, and ὁμοίωμα in the LXX in light of Greek literary and documentary evidence. By addressing the issue of the relationship between the vocabulary of images and the vocabulary of idols, (1) it deconstructs some oppositions inherited from early Christian interpretations of biblical passages (especially regarding Genesis 1). Moreover (2) it shows the interest of including evidence from the LXX in a broader discussion on the role of visual representation in antiquity.

As manifested in Jean Baudrillard’s notoriously provoking claim that “the Gulf War did not take place,” mediatization of war has long been associated with illusion. Today, war images that circulate online are increasingly judged by their proximity to ‘truth,’ eliciting a skepticism towards their ‘evidentiary’ value. By juxtaposing Baudrillard’s reading of the mediatization of the Gulf War with the contemporary image theories of e.g. Cecilia Sjöholm and Matthew Fuller and Eyal Weizman, the article explores how this skepticism is expressed in a contemporary context. Through visual analysis of a YouTube video of a press conference held at the bombed Al-Ahli Baptist Hospital in Gaza, it examines the relationship between the f orm through which the war is perceived (the images) and their cont ent (the ‘realities’ of war). Through a lens oered by Georges Didi-Huberman, the article concludes by suggesting that by expanding what I term the snapshot logic of war images to embrace a scenography of war, the press conference video gives form to the condition of desperation and suering in Gaza.

In recent years, artificial intelligence (AI), especially deep learning models, has increasingly been integrated into diagnosing and treating diabetic retinopathy (DR). From delving into the singular realm of ocular fundus photography to the gradual development of proteomics and other molecular approaches, from machine learning (ML) to deep learning (DL), the journey has seen a transition from a binary diagnosis of “presence or absence” to the capability of discerning the progression and severity of DR based on images from various stages of the disease course. Since the FDA approval of IDx-DR in 2018, a plethora of AI models has mushroomed, gradually gaining recognition through a myriad of clinical trials and validations. AI has greatly improved early DR detection, and we’re nearing the use of AI in telemedicine to tackle medical resource shortages and health inequities in various areas. This comprehensive review meticulously analyzes the literature and clinical trials of recent years, highlighting key AI models for DR diagnosis and treatment, including their theoretical bases, features, applicability, and addressing current challenges like bias, transparency, and ethics. It also presents a prospective outlook on the future development in this domain.