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PurposeThe purpose of this paper is to examine the current state of Linked Data (LD) in archival moving image description, and propose ways in which current metadata records can be enriched and enhanced by interlinking such metadata with relevant information found in other data sets.Design/methodology/approachSeveral possible metadata models for moving image production and archiving are considered, including models from records management, digital curation, and the recent BIBFRAME AV Modeling Study. This research also explores how mappings between archival moving image records and relevant external data sources might be drawn, and what gaps exist between current vocabularies and what is needed to record and make accessible the full lifecycle of archiving through production, use, and reuse.FindingsThe author notes several major impediments to implementation of LD for archival moving images. The various pieces of information about creators, places, and events found in moving image records are not easily connected to relevant information in other sources because they are often not semantically defined within the record and can be hidden in unstructured fields. Libraries, archives, and museums must work on aligning the various vocabularies and schemas of potential value for archival moving image description to enable interlinking between vocabularies currently in use and those which are used by external data sets. Alignment of vocabularies is often complicated by mismatches in granularity between vocabularies.Research limitations/implicationsThe focus is on how these models inform functional requirements for access and other archival activities, and how the field might benefit from having a common metadata model for critical archival descriptive activities.Practical implicationsBy having a shared model, archivists may more easily align current vocabularies and develop new vocabularies and schemas to address the needs of moving image data creators and scholars.Originality/valueMoving image archives, like other cultural institutions with significant heritage holdings, can benefit tremendously from investing in the semantic definition of information found in their information databases. While commercial entities such as search engines and data providers have already embraced the opportunities that semantic search provides for resource discovery, most non-commercial entities are just beginning to do so. Thus, this research addresses the benefits and challenges of enriching and enhancing archival moving image records with semantically defined information via LD.

We present a diffeomorphic image registration algorithm to learn spatial transformations between pairs of images to be registered using fully convolutional networks (FCNs) under a self‐supervised learning setting. Particularly, a deep neural network is trained to estimate diffeomorphic spatial transformations between pairs of images by maximizing an image‐wise similarity metric between fixed and warped moving images, similar to those adopted in conventional image registration algorithms. The network is implemented in a multi‐resolution image registration framework to optimize and learn spatial transformations at different image resolutions jointly and incrementally with deep self‐supervision in order to better handle large deformation between images. A spatial Gaussian smoothing kernel is integrated with the FCNs to yield sufficiently smooth deformation fields for diffeomorphic image registration. The spatial transformations learned at coarser resolutions are utilized to warp the moving image, which is subsequently used as input to the network for learning incremental transformations at finer resolutions. This procedure proceeds recursively to the full image resolution and the accumulated transformations serve as the final transformation to warp the moving image at the finest resolution. Experimental results for registering high‐resolution 3D structural brain magnetic resonance (MR) images have demonstrated that image registration networks trained by our method obtain robust, diffeomorphic image registration results within seconds with improved accuracy compared with state‐of‐the‐art image registration algorithms. We present a diffeomorphic image registration algorithm to learn spatial transformations between pairs of images to be registered using fully convolutional networks under a self‐supervised learning setting. Experimental results have demonstrated our method could obtain robust, diffeomorphic image registration results within seconds with improved accuracy compared with state‐of‐the‐art image registration algorithms.

En el campo de la documentación, una tarea fundamental para una eficaz recuperación de información por parte de los usuarios de los sistemas de información es el análisis de contenido. En la presente investigación analizamos el estado actual de esa tarea en seis importantes filmotecas españolas. Se ha entrevistado a sus responsables de documentación de fondos fílmicos y se ha hecho un análisis comparativo de los campos relativos al contenido fílmico dentro de las fichas de análisis documental aplicadas por cada una de estas seis instituciones sobre sus fondos fílmicos.

Within the framework of a “neurofilmological” approach – which integrates film studies, cognitive psychology, and neuroscience – the present study explored how cinematographic editing influences the viewer’s perception of time. Previous behavioral research has shown that editing density affects temporal judgments. To investigate the neural mechanisms underlying this relationship, we examined the role of motor system activity, specifically the supplementary motor area (SMA), in time perception when individuals are exposed to moving images with different cinematographic editing styles. Forty-eight university students were assigned to one of three tDCS conditions (anodal, cathodal, or sham). They viewed nine silent video clips with different editing styles (master shot, slow-paced, fast-paced) that were specifically created for research. The participants rated perceived duration, time passage, action speed, and emotional engagement, while tDCS was applied for 20 min targeting the SMA. The results revealed that SMA excitability modulation affected duration estimates, time passage, and action speed judgments by interacting with the editing style of the clips. These findings highlight the importance of the SMA in modulating time perception during film viewing. Furthermore, they provide valuable insights into the neural mechanisms that shape the viewer’s perception of film time as an integral part of experiencing movement in cinema.

The combined behaviours of individuals within insect societies determine the survival and development of the colony. For the western honey bee ( Apis mellifera ), individual behaviours include nest building, foraging, storing and ripening food, nursing the brood, temperature regulation, hygiene and defence. However, the various behaviours inside the colony, especially within the cells, are hidden from sight, and until recently, were primarily described through texts and line drawings, which lack the dynamics of moving images. In this study, we provide a comprehensive source of online video material that offers a view of honey bee behaviour within comb cells, thereby providing a new mode of observation for the scientific community and the general public. We analysed long-term video recordings from longitudinally truncated cells, which allowed us to see sideways into the cells in the middle of a colony. Our qualitative study provides insight into worker behaviours, including the use of wax scales and existing nest material to remodel combs, storing pollen and nectar in cells, brood care and thermoregulation, and hygienic practices, such as cannibalism, grooming and surface cleaning. We reveal unique processes that have not been previously published, such as the rare mouth-to-mouth feeding by nurses to larvae as well as thermoregulation within cells containing the developing brood. With our unique video method, we are able to bring the processes of a fully functioning social insect colony into classrooms and homes, facilitating ecological awareness in modern times. We provide new details and images that will help scientists test their hypotheses on social behaviours. In addition, we encourage the non-commercial use of our material to educate beekeepers, the media and the public and, in turn, call attention to the general decline of insect biomass and diversity.

This study explores attitudes of moving image archivists and digital projects managers toward the digitization and online distribution of archival moving image materials. The primary method for gathering data about this subject was through in-depth interviewing of individuals who have managed moving image digitization projects in archival settings. The investigator discusses challenges in launching and sustaining digital projects and the evolving audience for archival moving images. Archivists also must reconcile their desire to provide more access with concerns about quality of digital surrogates, legal restrictions such as copyright, and how online distribution may impact relations with creators, donors, and content owners.

The absence of the encounter-this is the claim I wish to advance and explore here-stems instead from a set of fundamental impediments (a denial of the reality of images, the exclusion of time and movement from aesthetic experience) that render the standpoint of OOP incapable of producing constructive effects in the domain of film theoretical research. [...]the question is not simply that of the possibility or impossibility of the application of OOP's concepts to cinema as the object of study.

Dynamic chest radiography (DCR) is a real-time sequential high-resolution digital X-ray imaging system of the thorax in motion over the respiratory cycle, utilising pulsed image exposure and a larger field of view than fluoroscopy coupled with a low radiation dose, where post-acquisition image processing by computer algorithm automatically characterises the motion of thoracic structures. We conducted a systematic review of the literature and found 29 relevant publications describing its use in humans including the assessment of diaphragm and chest wall motion, measurement of pulmonary ventilation and perfusion, and the assessment of airway narrowing. Work is ongoing in several other areas including assessment of diaphragmatic paralysis. We assess the findings, methodology and limitations of DCR, and we discuss the current and future roles of this promising medical imaging technology.Critical relevance statement Dynamic chest radiography provides a wealth of clinical information, but further research is required to identify its clinical niche.Key pointsDynamic chest radiography (DCR) captures high-resolution moving images of the thorax.The ionising radiation dose of DCR is low.DCR can image the diaphragm, chest wall, ventilation and perfusion.Most papers on DCR are small, with heterogeneity in study design or outcome.Large, multicentre studies with similar outcomes and healthy controls are desirable.

Long waits online undermine users' evaluations of Web sites and their providers, triggering abandonment behaviors. Yet e-business researchers and practitioners have not perfected mechanisms to respond to online wait issues. A filler interface that runs during the wait for search results may influence online users' perceived waiting time (PWT); however, no scientific investigation has attempted to design effective filler interfaces for managing online waits. By adopting resource allocation theory, cognitive absorption theory, and human computer interaction (HCI) theories (competition for attention, visual search, and motion effect), we design diverse filler interfaces and investigate their effects on antecedents of PWT. The proposed research model considers cognitive absorption factors such as temporal dissociation, focused immersion, and heightened enjoyment as antecedents of PWT, which in turn triggers three outcomes: affective appraisals, cognitive appraisals, and Web site use intention. A multistage, multimethod approach is used to test the research hypotheses. In the first stage, we compare a filler interface condition with a no-filler interface condition, and find the superiority of a filler interface with respect to inducing focused immersion and temporal dissociation. In the second stage, we conduct two controlled experiments to examine whether filler interfaces with various designs (varying the presence and relevance of image, text, and image motion) distinctly influence antecedents of PWT and confirm their distinctive effects on focused immersion, temporal dissociation, and heightened enjoyment. In addition, by conducting a structural equation modeling analysis, we find that our research model explains 51 percent, 51 percent, 44 percent, and 45 percent of the variance in PWT, affective appraisals, cognitive appraisals, and Web site use intention respectively. Theoretical and practical implications of these findings are provided.

Random noise-moving images (noises) can make glaucoma patients with no subjective symptoms aware of visual field abnormalities. To explore this concept, we developed a noise using computer graphics (CG) and investigated the difference in the subjective perception of visual field abnormalities between CG and conventional analog noises. We enrolled individuals with glaucoma (205 eyes), preperimetric glaucoma (PPG; 19 eyes), and normal eyes (35 eyes). For a CG noise, a series of still images was made by randomly selecting five monochromatic tones on 2-mm square dots, and these images were drawn at 60 frames per second (fps) to create a noise-moving image. The participants were asked to describe their perceived shadows on a paper. The results were categorized as follows based on the pattern deviation probability map of the Humphrey field analyzer (HFA): \"agreement,\" \"partial agreement,\" \"disagreement,\" and \"no response.\" The glaucoma stage was classified into four stages, from M1 to M4, based on the HFA's mean deviation. The detection rates (agreement and partial agreement) were 80.5% and 65.4% for the CG and analog noises, respectively, with CG noise showing a significantly higher detection rate in all glaucoma eyes (P < 0.001). The detection rates tended to increase as the glaucoma stage progressed, and in Stage M3, these were 93.9% and 78.8% for the CG and analog noises, respectively. The PPG eyes did not exhibit subjective abnormalities for both noises. The specificity values were 97.1% and 100% for the CG and analog noises, respectively. The CG noise is more effective than the analog noise in evaluating the subjective perception of visual field abnormalities in patients with glaucoma.