Single Pictures Research Articles

Invisible Images: Pictures, Illustrations and Visual Data in the Text-Centric System of the Library

This study investigates how the library information infrastructure steers not only the access, searchability and retrievability of the images it preserves but also, on a more profound level, how images are understood as sources of information. Using the National Library of Sweden as a case study it first outlines how images are handled and conceptualized – as single pictures, as illustrations secondary to text, or as visual data, repositories of iconographic visual content. Second, through close analysis of five types of images common in library collections in general, it examines how they are classified, demarcated and made accessible. As this study shows, both analogue and digital information infrastructures in the library are, on a very profound level, tailored for text. Such unuttered, even unconscious, text-centrism has the effect that images as sources of information are made literally and figuratively invisible.

Comparison of micro- and macro- structural narrative features between Turkish-Kurdish bilinguals and Turkish monolinguals

Abstract Bilingualism may lead to differences in narrative micro- and macrostructural features. Creating a normative data set on the narrative characteristics of healthy Turkish-Kurdish bilinguals may allow for a more effective assessment of language disorders that may occur in bilinguals with acquired brain injury. This study aims to determine how narrative micro- and macrostructural features differ in Turkish-Kurdish bilinguals in single picture and story narratives. A total of 23 bilingual (Turkish-Kurdish) and 23 monolingual (Turkish) healthy individuals were included in the study. Narrative samples were obtained using single pictures and a story. Micro- and macrostructural features were compared between bilinguals and monolinguals matched for age, education, and gender. Mean length utterance-morpheme and clausal density variables, considered as indicators of grammatical complexity, were higher in monolinguals in both single picture and story narratives. Morphemic errors were higher for bilinguals. Effort behaviors, which can interrupt verbal efficiency, were higher in bilinguals in single picture narratives. While there was no difference between the groups in verbal fluency (phonemic and categorical), the lexical diversty in storytelling was higher in monolinguals. In terms of macrostructural features, cognitive inferences in the story context and emotional discourse in the single picture context were higher in monolinguals, while enrichment expressions in the single picture narrative were higher in bilinguals. In both groups, macrostructural features such as cognitive inferences and expressions of uncertainty in discourse were negatively correlated with grammatical complexity variables. Turkish-Kurdish bilinguals’ single picture and story narratives in Turkish may show semantic, morphosyntactic and pragmatic differences compared to Turkish-speaking monolinguals.

Reproducibility of SIMPLE classification for diabetic retinopathy screening and its comparison to current Italian guidelines.

To evaluate the reproducibility of SIMPLE (Single field Image Multi Parameters defined Lesions Extent), a new Diabetic Retinopathy (DR) classification for screening of 45° single field fundus pictures of patients with diabetes (PwDM), assessing DR, Diabetic Maculopathy (DMac) and referral rate agreement and comparing it to current Italian Guidelines (IG). We conducted a retrospective, observational, multicentre study, collecting 1000 retinal 45° single field images of PwDM obtained during routine visits in two diabetes clinics. Three ophthalmologists evaluated each image, determining the presence and number of specific DR lesions and then assigning a stage according to the current IG for screening. SIMPLE staging was performed automatically via Excel software, based on the pre-specified DR characteristics observed by the graders. We analysed intra-centre, inter-centre and total inter-grader agreement for DR and DMac stage and referral rate of the two classifications. Agreement amongst the three graders was consistently higher when using SIMPLE classification than when using current IG classification. For DR, kappa (k) was 0.86 with IG and 0.95 with SIMPLE classification; for DMac, k-IG was 0.78, while k-SIMPLE was 0.96; concordance on the referral rate was 0.91 with IG and 0.99 with SIMPLE. Similar results were obtained in sub-analyses for the evaluation of intra-centre and inter-centre concordance. Our results suggest that the new SIMPLE classification has an excellent reproducibility amongst graders, comparable or superior to the current IG for DR screening proposed in 2015, improving the standardisation of the decision on referability.

Item-method directed forgetting and perceived truth of news headlines

ABSTRACT Research on item-method directed forgetting (IMDF) suggests that memories can be voluntarily forgotten. IMDF is however usually examined with relatively simple study materials, such as single words or pictures. In the present study, we examined voluntary forgetting of news headlines from (presumably) untrustworthy sources. Experiment 1 found intact IMDF when to-be-forgotten headlines were characterised as untrustworthy and to-be-remembered headlines were characterised as trustworthy. Experiment 2 separated remember/forget cues and trustworthiness prompts. Forget cues alone had a large effect on memory, but only a small reducing effect on perceived truth. In contrast, trustworthiness prompts alone had essentially no effect on memory, but a large effect on perceived truth. Finally, Experiment 3 fully crossed forget/remember cues and trustworthiness prompts, revealing that forget cues can reduce memory irrespective of whether headlines are characterised as trustworthy or untrustworthy. Moreover, forget cues may bias source attributions, which can explain their small reducing effect on perceived truth. Overall, this work suggests that news headlines can be voluntarily forgotten. At least when people are motivated to forget information from untrustworthy sources, such forgetting may be helpful for curtailing the spread of false information.

Quantity Processing in Object Counting Task Based on Event-Related Potentials

In the preliminary event-dependent potentials study, our team found that the neural mechanism of Chinese singular and plural picture naming is different, and explained that the differences might lie in the different numbers of quantitative processing. However, previous studies have lacked separate neural processing of objects in singular-plural pictures. This study intends to explore the neural differences in quantity processing in singular and plural pictures by using an object counting task and combining Event-related potential (ERP). It is expected to prove that the neural differences of naming Chinese single and plural pictures found in our previous ERP research are neural processing differences of different quantities, further demonstrating that the quantity processing in Chinese singular and plural picture naming is automatic. The experimental results showed no significant differences in object counting accuracy (P=0.139) and reaction time (P=0.231) between the singular and plural groups. However, there was a noticeable difference in ERPs between the two groups (P<0.05) and statistical analysis showed that the P1 effect of the parieto-occipital lobe was greater in plural pictures than in singular pictures (140-180ms) and the P2 effect of the parieto-occipital lobe was more significant in singular pictures than in plural pictures (200-320ms). There are differences in the quantity processing of healthy adults in object counting tasks. These differences are similar to the neural differences in Chinese singular-plural picture naming, indicating that the quantity is automatically processed in this process.

Optimal segmentation and fusion of multi-modal brain images using clustering based deep learning algorithm

In the last several years, the world of medical technology has seen a boom in multimodal picture fusion. Information is constrained since a single medical instrument can only acquire single modal pictures. Doctors often need a large number of multimodal pictures to get the complete information necessary for disease diagnosis. The burden associated with illness diagnosis will significantly rise when multimodal pictures are employed directly, and errors and interference are likely to occur. Fusion algorithms, which have been extensively employed in the medical industry, may very effectively combine a lot of information in multimodal pictures. However, the existing method has an issue with the earlier stages of brain tumor prediction in white images and inaccuracy image results. To overcome the above-mentioned problems, in this work, Adaptive Firefly Optimization based Convolutional Neural Network (AFFOCNN) and Modified Fully Connected Layer (MFCL) scheme is proposed. This work contains main steps such as noise removal, segmentation, feature extraction, image fusion, and image classification process. Initially, noise removal is done for improving the image quality by removing the noise. Then the modality MRI images are segmented and it is used for subdividing an image into its constituent regions or object. It segments the image into black and white images. After that, feature extraction is applied through the AFFOCNN algorithm which extracts the more informative image features. Image fusion of multi-modal images derived the lower-level, middle-level, and higher-level image contents. It can be viewed in multiple directions and fused in all directions. Finally, image classification is performed by using a Modified Fully Connected Layer (MFCL) which improves the training and testing features efficiently. It was determined from the results that the suggested combination of AFFOCN and MFCL algorithm performs improved than the current algorithms with the increased accuracy, precision, recall, and mean square error (MSE), as well as execution time with the values of 99.00%, 98.00%, 96.00%, 12.00% and 2.40 seconds respectively.

Picnic, Accident or Cookies? A Systematic Approach to Guide the Selection of the Picture Definition Tasks in Linguistic Assessment

Picture description tasks are used to elicit language samples in individuals with aphasia and other cognitive disorders. However, task selection may affect the type of language variables elicited. In this study, our goal is to compare the strengths and the weaknesses of the two internationally used picture description tasks with a novel picture description task developed specifically for Turkish-speaking individuals. In sum, 20 cognitively healthy individuals with a mean age of 52 ± 14/3 were included. Three different picture description tasks composed of single pictures were used: The Picnic Scene from the Western Aphasia Battery-Revised, the Cookie Theft picture from the Boston Diagnostic Aphasia Examination and the Accident Scene from the Turkish Language Assessment Test for Aphasia. All language samples were recorded using a digital voice recorder. Automated and semi-automated approaches were used for the systematic analysis of the language features that were classified into four levels: general language measures, the morphosyntactic level, the lexicosemantic level and the sentence level. Participants showed greater efficiency and produced the greatest number of subordinate clauses, derivational suffixes, passive voice suffixes and relative past tense construction during the Accident Scene description. On the lexicosemantic level, the Picnic Scene was particularly superior to the Cookie Theft Picture in eliciting nouns. Imperfective aspect use was less frequent in the Accident Scene description. All three tasks had limitations and advantages compared with each other. We recommend the development of novel picture description tasks that would be more effective in eliciting specific language features in Turkish-speaking individuals.

Representation of others' synchronous and asynchronous sentences interferes with sentence production.

In dialogue, people represent each other's utterances to take turns and communicate successfully. In previous work, speakers who were naming single pictures or picture pairs represented whether another speaker was engaged in the same task (vs a different or no task) concurrently but did not represent in detail the content of the other speaker's utterance. Here, we investigate the co-representation of whole sentences. In three experiments, pairs of speakers imagined each other producing active or passive descriptions of transitive events. Speakers took longer to begin speaking when they believed their partner was also preparing to speak, compared to when they did not. Interference occurred when speakers believed their partners were preparing to speak at the same time as them (synchronous production and co-representation; Experiment 1), and also when speakers believed that their partner would speak only after them (asynchronous production and co-representation; Experiments 2a and 2b). However, interference was generally no greater when speakers believed their partner was preparing a different compared to a similar utterance, providing no consistent evidence that speakers represented what their partners were preparing to say. Taken together, these findings indicate that speakers can represent another's intention to speak even as they are themselves preparing to speak, but that such representation tends to lack detail.

View VULMA: Data Set for Training a Machine-Learning Tool for a Fast Vulnerability Analysis of Existing Buildings

The paper presents View VULMA, a data set specifically designed for training machine-learning tools for elaborating fast vulnerability analysis of existing buildings. Such tools require supervised training via an extensive set of building imagery, for which several typological parameters should be defined, with a proper label assigned to each sample on a per-parameter basis. Thus, it is clear how defining an adequate training data set plays a key role, and several aspects should be considered, such as data availability, preprocessing, augmentation and balancing according to the selected labels. In this paper, we highlight all these issues, describing the pursued strategies to elaborate a reliable data set. In particular, a detailed description of both requirements (e.g., scale and resolution of images, evaluation parameters and data heterogeneity) and the steps followed to define View VULMA are provided, starting from the data assessment (which allowed to reduce the initial sample of about 20.000 images to a subset of about 3.000 pictures), to achieve the goal of training a transfer-learning-based automated tool for fast estimation of the vulnerability of existing buildings from single pictures.

Pauli crystals in harmonic trap and on a sphere

We study configurations maximizing N-particle probability distributions of non-interacting particles obeying Fermi statistics as discussed in [1]. We consider two different types of particles' confinement: (i) trapping in a harmonic potential and (ii) constraining to the surface of a sphere. In such settings the most probable arrangements of particles correspond to characteristic geometric patterns resulting from the combined effect of confinement and the Pauli exclusion principle. We discuss the geometry of these optimal configurations as well as two different methods of extracting these shapes from a number of single shot pictures of the system. The post-selection method which does not assume a priori any information on the optimal configurations is illustrated in detail.

Selection of Key Frames for 3D Reconstruction in Real Time

Cameras play a prominent role in the context of 3D data, as they can be designed to be very cheap and small and can therefore be used in many 3D reconstruction systems. Typical cameras capture video at 20 to 60 frames per second, resulting in a high number of frames to select from for 3D reconstruction. Many frames are unsuited for reconstruction as they suffer from motion blur or show too little variation compared to other frames. The camera used within this work has built-in inertial sensors. What if one could use the built-in inertial sensors to select a set of key frames well-suited for 3D reconstruction, free from motion blur and redundancy, in real time? A random forest classifier (RF) is trained by inertial data to determine frames without motion blur and to reduce redundancy. Frames are analyzed by the fast Fourier transformation and Lucas–Kanade method to detect motion blur and moving features in frames to label those correctly to train the RF. We achieve a classifier that omits successfully redundant frames and preserves frames with the required quality but exhibits an unsatisfied performance with respect to ideal frames. A 3D reconstruction by Meshroom shows a better result with selected key frames by the classifier. By extracting frames from video, one can comfortably scan objects and scenes without taking single pictures. Our proposed method automatically extracts the best frames in real time without using complex image-processing algorithms.

A Survey of Multi-Modal Image Fusion Methodologies

Digital image fusion has advanced significantly in governments and civil domains since its introduction in the late 1980s, certainly image fusion of infrared light, materials characterization, remote sensing data fusion, visions segmentation techniques, and brain tumor detection fusion. In medical diagnostics, imaging technology is critical. Because single medical pictures cannot match the demands of diagnostic techniques, which necessitate a huge quantity of data, image fusion study has become a hot subject. Single-mode integration and multi - modal fusion is the two types of medical image processing. Due to the limitations of single-modal fusion's data, many scientists are investigating multidimensional fusion. Brain tumor detection fusion represents the operations of integrating multiple images from imaging modality to formulate fused images with larger volume of data, allowing medical images to be more clinically useful. In this article, we focus on providing a survey of multi-modal image fusion approaches with central focus on novel developments in the domain based on the present fusion approaches, incorporating deep learning fusion approaches. Lastly, this concludes that contemporary multi-modal image fusion study findings are significantly fundamental, and the development trends is on the increase, however there are several hurdles in the study area.

“Telling in Time” Extended

Temporality has long been recognized as a defining trait of narrative. This article introduces new concepts, methods, and arguments to analyze the relationships between represented and representational timelines for a transmedia narratology with a strong focus on emotions, rethinking such fundamental concepts as complication, resolution, and illustration. Since Gotthold Ephraim Lessing (1766) distinguished the temporal arts like poetry, where signs are consecutive, from the spatial arts like painting, where signs are juxtaposed, the latter have been considered to be limited when it comes to conveying stories autonomously. Opposing this point of view, this article explains how monochronic pictures can convey timelines by relying on the depiction of traces, as well as an appeal to anthropological and cultural knowledge. It then shows how some monochronic pictures intended as illustrations sometimes convey stories autonomously. The author argues based on a choice of photographs that inducing suspense or curiosity is possible even through a monochronic picture. The article also shows how single pictures induce experiences of duration or instantaneity, concluding that single monochronic pictures can convey essential story events in a predetermined order and reliably convey the timeline of these events. This implies that such single pictures can be narratives even according to narrow definitions of the concept.

Unitization could facilitate item recognition but inhibit verbatim recognition for picture stimuli: behavioral and event-related potential study.

It is widely accepted that unitization can promote familiarity-based associative recognition, but the effect of unitization on item recognition remains unclear. The goals of this study were to elaborate on how unitization affected item recognition and the neural correlates of familiarity and recollection for item recognition. In study, the participants were asked to learn related and unrelated picture pairs, and in test, they were required to distinguish single old pictures form new pictures. In experiment 1, we used R/K/N paradigm to estimate the contribution of familiarity and recollection to item recognition, the results showed that unitization could improve item recognition through increasing recollection selectively. In experiment 2, we used ERP old/new effects to estimate the neural correlates of familiarity and recollection, the results showed that unitization could improve item recognition through a selective reduction in LPC effect. Inspired by DRM paradigm, in experiment 3, we divided the new pictures into semantically related lure pictures and semantically unrelated new pictures to explore the effects of unitization on item recognition and verbatim recognition (the ability to distinguish old pictures from lure pictures). The behavioral results showed that unitization could improve item recognition, but it damaged verbatim recognition. The ERP results revealed that there were larger LPC effects in the unrelated condition than in the related condition, regardless of item or verbatim recognition. In summary, we believed that unitization could indeed improve item recognition, but it damaged verbatim recognition.

Attention towards food: Conflicting mechanisms in anorexia nervosa

In Anorexia nervosa (AN) attentional biases towards, as well as away from, food cues have been found using different paradigms. In the current study, adult and adolescent AN patients and control participants performed two tasks while their eye movements were recorded. The tasks involved viewing and rating: 1. Single photographs of food items; 2. Pairs of pictures consisting of one picture of high calorie and one of low calorie food. Girls and women suffering from AN rated pictures of high calorie food as more negative than control participants. In the task showing single food pictures, reduced fixation times within Regions of Interest of low calorie food were seen in AN; during the task using picture pairs, a visual attentional bias towards low calorie and away from high calorie stimuli for AN was demonstrated. There is evidence for heightened visual attentional capture by high calorie stimuli when presented alone as well as attraction of attention by low calorie stimuli when shown next to high calorie stimuli, possibly facilitated by avoidance of the latter. Different attentional mechanisms seem to be activated when only one stimulus is shown compared to when two stimuli are competing for the viewer's attention.

Seeing different motifs in one picture: Identifying ambiguous figures in South Scandinavian Bronze Age rock art

Ambiguous figures, as described in visual perceptual psychology, are single pictures that contain several possible, mutually exclusive, motifs. When looking at a rock-art panel, petroglyphs at a fi...

Distribution of attention in a gallery segment on the National Socialists’ Führer cult: diving deeper into visitors’ cognitive exhibition experiences using mobile eye tracking

ABSTRACTMobile eye tracking recordings of 20 visitors of the gallery section ‘Der Führer’ of the Dokumentation Obersalzberg (Germany) were analyzed to determine the distribution of the visitors’ attention on a detailed level of individual exhibition elements consisting of single objects, pictures, texts, and labels. It was found that most of these elements were only briefly scanned but with a substantial variability in gaze behavior both across participants and exhibition elements. In particular, the objects and pictures primarily attracted the visitors’ attention but did not necessarily lead to elaborate inspection. In contrast, the information texts were less often noticed by the visitors, but if they were noticed, the visitors tended to spend substantial time reading them. The study demonstrates that notwithstanding methodological drawbacks such as the lack of unobtrusiveness of recording or highly time-consuming coding of raw data, mobile eye tracking allows to analyze visitors’ attention in a gallery with unprecedented precision.

Brain Tumor Detection and Segmentation using Histogram and Optimization Algorithm

In this research, an automated and customized neoplasm segmentation methodology is given and valid against ground truth applying simulated T1-weighted resonance pictures in twenty five subjects. a replacement intensity-based segmentation technique known as bar graph primarily based gravitational optimization algorithm is developed to segment the brain image into discriminative sections (segments) with high accuracy. whereas the mathematical foundation of this rule is given in details, the appliance of the projected rule within the segmentation of single T1-weighted pictures (T1-w) modality of healthy and lesion MR images is additionally given. The results show that the neoplasm lesion is divided from the detected lesion slice with eighty nine.6% accuracy..

Identifying Cortical Substrates Underlying the Phenomenology of Stereopsis and Realness: A Pilot fMRI Study.

Viewing a real scene or a stereoscopic image (e.g., 3D movies) with both eyes yields a vivid subjective impression of object solidity, tangibility, immersive negative space and sense of realness; something that is not experienced when viewing single pictures of 3D scenes normally with both eyes. This phenomenology, sometimes referred to as stereopsis, is conventionally ascribed to the derivation of depth from the differences in the two eye’s images (binocular disparity). Here we report on a pilot study designed to explore if dissociable neural activity associated with the phenomenology of realness can be localized in the cortex. In order to dissociate subjective impression from disparity processing, we capitalized on the finding that the impression of realness associated with stereoscopic viewing can also be generated when viewing a single picture of a 3D scene with one eye through an aperture. Under a blocked fMRI design, subjects viewed intact and scrambled images of natural 3-D objects, and scenes under three viewing conditions: (1) single pictures viewed normally with both eyes (binocular); (2) single pictures viewed with one eye through an aperture (monocular-aperture); and (3) stereoscopic anaglyph images of the same scenes viewed with both eyes (binocular stereopsis). Fixed-effects GLM contrasts aimed at isolating the phenomenology of stereopsis demonstrated a selective recruitment of similar posterior parietal regions for both monocular and binocular stereopsis conditions. Our findings provide preliminary evidence that the cortical processing underlying the subjective impression of realness may be dissociable and distinct from the derivation of depth from disparity.

What narrative is

AbstractUnacknowledged by its practitioners, narratology has often been revisionary rather than descriptive when categorizing narratives. This is becausedefinitions, expert judgmentandpersonal intuition, traditionally the main tools for categorization, are vulnerable to media blindness and to being theory loaded. I argue that to avoid revisionary accounts of ordinary everyday practices such as narrative or gameplay of which non-experts have a firm understanding, expert categorizations have to be tested against folk intuitions as they become apparent in ordinary language. Pictorial narrative in single pictures is introduced as a specific case of categorization dispute and an experiment laid out in which non-experts assess if different pictures tell stories. As the chosen pictures correspond to different criteria of narrative to varying degrees, the experiment also serves as an implicit test of these criteria. Its results confirm monochrony compatibilism, the position that single monochronic pictures can autonomously convey stories. While the pictures rated high in narrativity correspond to traditional criteria of narrative, I argue that the way in which these criteria are usually interpreted by narratologists is problematic because they exclude these pictures from the realm of narratives. It is argued that the way marginal phenomena are categorized is essential for a sound understanding of even the most paradigmatic objects of a domain because categorizations influence definitions and definitions ultimately guide interpretations.