Images Of Animals Research Articles

Animal Images in Shamanic Cult and Attributes in Traditional Yakut Culture

The purpose of this article is to systematize and define the role of the animal world in the mythology of Yakut shamanism and its attributes. The topic of shamanism was studied earlier mainly from an anthropocentric point of view. At present, it is interesting to consider the role of animal images in the shamanic cult and the way their communication with the shaman takes place. The sources of the study were archival and published ethnographic and folklore materials on traditional Yakut beliefs. With their help the plots in which animals appear as patron spirits, spirit-helpers and symbolic images were revealed. The animal image of the shamanic patron spirit – “iye-kyyl” (mother-beast) which participates in the “birth” of the shaman was considered. We also paid attention to animals acting as helper spirits directly in contact with the shaman: they ensure his mobility in supernatural spaces and share their powers and abilities with him. The material use of animal images for magical and apotropaic purposes in the shaman’s paraphernalia is touched upon. The methodological basis of the study is the actor-network theory and the symbolic approach. As a result of the study, we conclude that in Yakut shamanism animal images play a significant role of intermediaries between shamans and supernatural spaces. The study reveals the ideas that spirits act in an active capacity: they do not simply carry functional roles, but are themselves the initiators of the supernatural spaces.

Neuronal tuning and population representations of shape and category in human visual cortex

Object recognition and categorization are essential cognitive processes which engage considerable neural resources in the human ventral visual stream. However, the tuning properties of human ventral stream neurons for object shape and category are virtually unknown. We performed large-scale recordings of spiking activity in human Lateral Occipital Complex in response to stimuli in which the shape dimension was dissociated from the category dimension. Consistent with studies in nonhuman primates, the neuronal representations were primarily shape-based, although we also observed category-like encoding for images of animals. Surprisingly, linear decoders could reliably classify stimulus category even in data sets that were entirely shape-based. In addition, many recording sites showed an interaction between shape and category tuning. These results represent a detailed study on shape and category coding at the neuronal level in the human ventral visual stream, furnishing essential evidence that reconciles human imaging and macaque single-cell studies.

PHRASEOLOGICAL UNITS WITH A ZOONYMIC COMPONENT THAT CHARACTERIZE THE CHARACTER OF A PERSON IN THE KAZAKH AND ENGLISH LANGUAGES

The article deals with phraseological units with zoonymic components that characterize the character of a person in the Kazakh and English languages, explores linguistic expressive means using animal images to describe human qualities and behavioral characteristics. In the work, we will review phraseological units with zoonymic components in both languages and analyze them using a comparative method.The purpose of the scientific article is to identify similarities and differences in the description of the peculiarities of the use of phraseological units, analysis of phraseological units with zoonimic components in Kazakh and English languages in the discourse of representatives of the two cultures.The main section of the article proves that phraseological units with zoonymic components are a reflection of cultural characteristics and views on human character in the Kazakh and English languages. The analysis showed that phraseological units with animals to describe human qualities are used in the two languages. Phraseological units in the Kazakh language are closely related to animals, that is zoonyms reffered to livestock, while English language mainly relies on zoonyms related to birds, insects and sea creatures. The results of the study may be useful to linguists, translators and cultural scientists who study the interaction of language and culture.The relevance of the research topic was the comparative analysis of phraseological phrases with zoonymic components in the Kazakh and English languages, revealing similarities and differences in the way, how human character is perceived and described by the different representatives of cultures. The authors presented their own vision of the problems based on the analysis of the works of the scientists on this topic. Comprehensive analysis of phraseological units with zoonymic components, which have become the main object of the article's research were carried out.

Review of researches and technologies applicable to digitalization of the process of assessing the exterior of meat and dairy animals

To increase the efficiency of livestock farming, scientists are developing information and communication technologies aimed at digitalizing the process of assessing the exterior of animals. This review should improve understanding of the development steps of systems applicable to the digitalization of animal conformation assessment using computer vision and deep learning neural networks. The search focused on several topics: computer vision systems; training datasets; image acquisition systems; deep learning models; neural networks for training; performance parameters and system evaluation. Machine vision is an innovative solution by combining sensors and neural networks, providing a non-contact way to assess livestock conditions as cameras can replace human observation. Two approaches are used to obtain three-dimensional images for digitalization tasks in animal husbandry: shooting animals using one 3D camera fixed in one place, and shooting from different points using several 3D cameras that record images of animals and individual parts of their bodies, such like an udder. The features extracted from the images, called dorsal features, are used as input to the models. The reviewed publications used a variety of deep learning models, including CNN, DNN, R-CNN, and SSD, depending on the task. Similarly, neural networks such as EfficientNet, ShapeNet, DeepLabCut and RefineDet have been mainly used for animal health monitoring, while GoogleNet, AlexNet, NasNet, CapsNet, LeNet and ERFNet are mainly used for identification purposes.

A novel DbneAlexnet with Gazelle Hunting Optimization Algorithm enabled wild animal detection in WMSN data communication in IoT environment

SummaryThe main goal of this strategy is to detect the occurrence of wild animals in farmsteads and human habitats using an improved deep learning in order to avoid loss of life and damage to agricultural crops. This paper formulates a technique for recognizing wild animals in an Internet of Things (IoT) environment utilizing deep batch normalized exponential linear unit AlexNet (DbneAlexnet) and the Gazelle Hunting Optimization Algorithm (GHOA). The IoT‐Multimedia Sensor Networks (WMSN) network is first simulated, with the IoT nodes capturing the images needed for wild animal identification. The suggested GHOA is used for routing, which sends the captured images to the base station (BS). The input wild animal image is transmitted to image preprocessing at the BS, where it is processed using the Weiner filter (WF) to remove undesirable noise from the image. The denoised output is sent into salient map extraction, which extracts salient map to determine the regions that are conspicuous or noticeable at every place in the field of vision and guides the selection of attended location. Finally, the saliency map is forwarded to DbneAlexnet for detecting the wild animals, where the DbneAlexnet is trained using proposed GHOA. The suggested GHOA algorithm is created by combining the Gazelle Optimization Algorithm (GOA) and the deer hunting optimization algorithm (DHOA). Furthermore, detection is appraised by precision, recall, and f1‐score, which provide values of 90.2%, 89.1%, and 89.6%, respectively.

An analysis of information segregation in parallel streams of a multi-stream convolutional neural network.

Visual information is processed in hierarchically organized parallel streams in the primate brain. In the present study, information segregation in parallel streams was examined by constructing a convolutional neural network with parallel architecture in all of the convolutional layers. Although filter weights for convolution were initially set to random values, color information was segregated from shape information in most model instances after training. Deletion of the color-related stream decreased recognition accuracy of animate images, whereas deletion of the shape-related stream decreased recognition accuracy of both animate and inanimate images. The results suggest that properties of filters and functions of a stream are spontaneously segregated in parallel streams of neural networks.

Virtual Reality Animation Interaction Design using Bayesian Physics-Informed Neural Network with Archimedes Optimization Algorithm Based Scene Modelling

Virtual Reality Animation Interaction Design is a dynamic field at the intersection of technology and creativity, where immersive experiences come to life through the fusion of animation and interactive design. There are some challenges involves in design of virtual Reality animation. The main challenge is animation image error involves in the design. To overcome this issue, present a Virtual Reality Animation Interaction Design Using Bayesian Physics-Informed Neural Network with Archimedes Optimization Algorithm Based scene modelling (VRAID-BPINN-AOA) is proposed. Initially, the animation images are collected from animation dataset. Then, the animation images are fed to pre-processing segment. In pre-processing segment, the noise of the image is removing layer by layer by utilizing adaptive-noise Augmented Kalman Filter (ANAKF). Then the pre-processed animation image is given for Feature extraction process. In Feature extraction, spatiotemporal features such as Object Position, velocity, Optical flow and Crowd Density are extracted by utilizing Multi-Level 2-D Quantum Wavelet Transform (ML2DQWT). Finally the extracted feature attributes are given to Bayesian physics-informed neural network (BPINN) for the prediction of error in the animation images. In general, BPINN does not express some adaption of optimization strategies for determining optimal parameters to promise accurate prediction of error. Therefore, Archimedes Optimization Algorithm (AOA) is proposed to optimize the parameter of BPINN .The proposed technique is implemented and efficacy of VRAID-BPINN-AOA technique is assessed by support of numerous performances such as Bit Error Rate, Design Rate, End to End Delay, Latency, and Transmission Rate. Proposed VRAID-BPINN-AOA method attains 28.56%, 26.67% and 25.67% lower Bit error rate and26.42%, 25.67% and 23.67% lower Design rate are compared with existing such as Virtual Interactive Animation Design with Restricted Boltzmann machine (VI-AD-RBM),Generative deep learning for visual animation in landscapes design using Generative adversarial network(GDL-VALD-GAN), and Hand interface using deep learning in immersive virtual reality using convolutional neural network(HID-LVIR-CNN)respectively.

Charles Plumier’s descriptions and drawings of Antillean birds (1687–1697)

French Minim friar Charles Plumier (1646−1704), well known for his work as a botanist and for his observations made during three expeditions to the West Indies between 1687 and 1697, produced an enormous body of iconographic material held by the Bibliothèque centrale du Muséum national d’Histoire naturelle in Paris. Among Plumier’s nearly 6,000 separate images of plants and animals made in the Antilles, birds are represented by 215 drawings, including whole specimens but also numerous detailed views of anatomy, osteological as well as internal soft parts. The bird drawings are here identified, described, and fully catalogued for the first time, and selected drawings are reproduced. Evidence is presented to emphasis the originality and scientific accuracy of Plumier’s accounts.

Animalism in the Design of Clothes of the ХХ and Early XXI Centuries

The article presents an overview and systematisation of fashion design projects using animalistic motifs. The purpose of the study is to identify the manifestations of animalistic images in costume and the differences in their meanings in different historical periods. The research methodology is based on the application of methods of source, art, aesthetic, structural and compositional analysis. The scientific novelty lies in highlighting the stages of animalism development in the twentieth – early twenty-first centuries and identifying its main manifestations in costume. The results of the study are based on empirical material from designers and fashion houses that actively used and developed animalism in their work. Conclusions. As a result of the study, we conclude that there are various ways of manifesting animalism in fashion design, from copying animal images entirely to introducing their individual parts into the design or using photographs and artistic images. And while in the early twentieth century, costumes used mostly elements of animal skin, fur and feathers, and exotic animals and birds emphasised the status of the elite strata of society, with the development of technology and the spread of mass production of clothing, imitation gradually became popular. The destruction of the natural environment and the dominance of the artificial one led to the spread of fashion inspired by wildlife. Gradually, a style direction in fashion design was formed, which is now considered «fantasy classics». Over time, animalistic motifs have become visual carriers of «eco-fashion» and «eco-consciousness», reminding us of the need for significant transformations in the global consciousness of humanity. The flourishing of animalism in recent decades reflects the socio-cultural trends in society. The symbolism and interpretation of animalistic images in costume design reflects the care and desire to preserve the natural heritage in a world that is increasingly influenced by technological development.

Z-Symbols in the Interpretation of the Semantics of the Configuration of S- and Г-Shaped Scythian Cheek-Pieces of the Eastern European Zone

The work deals with the issue of the regional specificity of the formation and development of the Dionysian cult and Orphic teachings, common in the Northern Black Sea region during the Greek colonization of the 6th–5th centuries BC. On the extensive Scythian archaeological material of the Eastern European zone, the design of horse headbands decorated with cult symbols of Dionysus-Zagreus is being studied. S-shaped and Г-shaped Scythian cheekpieces serve as an object of study to determine whether their configuration corresponds to the inscriptions of the initial letter in the Greek name Zagreus on bone plates from Olbia, which are the first epigraphic evidence of the penetration of the Orphic teaching into the Northern Black Sea region. The results reveal the semantic content of the shape of the Scythian cheekpieces, imitating the inscription of the letter zeta, the initial letter in the name of Dionysus Zagreus, or serving as the designation of number seven, a magical number for adherents of the Dionysian cult and Orphism as a religious and philosophical doctrine. The symbols of the Dionysian cult and the Orphic teachings, used by the Scythians in the manufacture of decorative elements for horse equipment, performed an apothropeic and mystical function for those initiated or close to this cult, or served as a certain distinctive sign in society. Further study of Scythian artifacts for the presence of Dionysian symbolism will allow us to trace the extent of the spread of the cult of Dionysus, as well as make a comparative description with other areas of the Scythian-Siberian world and reveal the semantic load of animal images in connection with the shape of products decorated in the Scythian animal style.

Application of Android-based Learning Media Applications for Primary Education

Today's learning media has improved considerably than ever before and English at this time is a very important need because English has become an International language. As a means of supporting these activities, cellular phones (cellphones) can be used where currently there are many people from various circles who own and use them. For this reason, researchers created an English learning media application for children based on multimedia and smartphones that is expected to support learning activities and be easy for children to understand. This application contains basic English materials, such as introduction to alphabets, families, numbers and others. This application is equipped with animated images and how to pronounce them in English as well as practice questions for learning the material. By using the Android platform, with this application, it is hoped that children can better understand material about English. The creation of this android-based English learning application uses Adobe Flash CS5 and Adobe Photoshop CS5 software to design application designs. The software used in the creation of this application is Android-SDK (Software Development Kit), JDK (Java Development Kit) installation package, Eclipse Indigo and this application is tested on Android emulators and some android smartphones.

Application of Android-based Learning Media Applications for Primary Education

Today's learning media has improved considerably than ever before and English at this time is a very important need because English has become an International language. As a means of supporting these activities, cellular phones (cellphones) can be used where currently there are many people from various circles who own and use them. For this reason, researchers created an English learning media application for children based on multimedia and smartphones that is expected to support learning activities and be easy for children to understand. This application contains basic English materials, such as introduction to alphabets, families, numbers and others. This application is equipped with animated images and how to pronounce them in English as well as practice questions for learning the material. By using the Android platform, with this application, it is hoped that children can better understand material about English. The creation of this android-based English learning application uses Adobe Flash CS5 and Adobe Photoshop CS5 software to design application designs. The software used in the creation of this application is Android-SDK (Software Development Kit), JDK (Java Development Kit) installation package, Eclipse Indigo and this application is tested on Android emulators and some android smartphones.

An exploration of the influence of animal and object categories on recall of item location following an incidental learning task.

The current study explores the role of attention in location memory for animals and objects. Participants completed an incidental learning task where they rated animals and objects with regard to either their ease of collection to win a scavenger hunt (Experiments 1a and b) or their distance from the centre of the computer screen (Experiment 2). The images of animals and objects were pseudo-randomly positioned on the screen in both experiments. After completing the incidental learning task (and a reverse counting distractor task), participants were then given a surprise location memory recall task. In the location memory recall task, items were shown in the centre of the screen and participants used the mouse to indicate the position the item had been shown during the incidental encoding task. The results of both experiments show that location memory for objects was more accurate than for animals. While we cannot definitively identify the mechanism responsible for the difference in the location memory of objects and animals, we propose that differences in the influence of object-based attention at encoding affect location memory when tested at recall.

A3C: An Image-Association-Based Computing Device Authentication Framework for People with Upper Extremity Impairments

Current computing device authentication often presents accessibility barriers for people with upper extremity impairments (UEI). In this paper, we present a framework called Accessible image-Association-based Authentication for Computing-devices (A3C) , a novel recognition-based graphical authentication framework specifically designed for people with UEI to authenticate to their computing devices. A3C requires users to provide a set of primary images that the user knows that are recognizable to them and subsequently associate each primary image with a secondary image. To evaluate the efficacy of the A3C framework, we instantiated the framework by implementing a version of A3C called A3C-FA , which uses images of faces of people the user knows as the primary image and animal images as the secondary image. We then performed three studies to evaluate A3C-FA: a shoulder-surfing attack study ( N=319 ), a close-adversary attack study ( N=268 ), and a usability study with people with UEI ( N=14 ). We found that A3C was robust against both shoulder-surfing and close-adversary attacks. We also performed a detailed study to evaluate the accessibility of A3C-FA. Our participants reported that A3C-FA was more usable and more secure than the authentication approaches with which they were familiar. Based on these findings, we suggest four areas of future research to further improve the design of A3C framework.

Reading history through animal imagery from pre–WWII British editorial cartoons: Gandhi’s anticolonial struggle during India’s civil disobedience movement (1930–1931)

ABSTRACT This article studies animal imagery published in pre-WWII British editorial cartoons offering constant updates about India’s Civil Disobedience movement (1930s) against British colonialism to uncover the processes through which the event and the people participating in it, both Indian political leaders and British administrators, were designated a particular animal symbol that popularly became associated with their identities in the long run. In other words, the article looks into the question of how animal images affect the iconography of historical personalities. The article will be an insight into defamiliarizing/deconstructing the events and people from this movement and then analyse how animals were used as substitutes for defining, explaining, and debating a concept, a human, an event, or a nationality in the cartoons published in British newspapers in those times. Consequently, I will explore satirical representations of everyday politics during the Civil Disobedience movement, thus offering the cultural history of the Raj in those times. As these editorial cartoons are published almost at the same time as the actual occurrence of events in the 1930s, they also give an insight into the prevalent colonial stereotypes, traditions, beliefs, humour, tolerance level, as well as ‘domestic politics, social themes,’ of the existing society (Kemnitz).

Transfer Learning Model Application for Rastrelliger brachysoma and R. kanagurta Image Classification Using Smartphone-Captured Images

Prior aquatic animal image classification research focused on distinguishing external features in controlled settings, utilizing either digital cameras or webcams. Identifying visually similar species, like Short mackerel (Rastrelliger brachysoma) and Indian mackerel (Rastrelliger kanagurta), is challenging without specialized knowledge. However, advancements in computer technology have paved the way for leveraging machine learning and deep learning systems to address such challenges. In this study, transfer learning techniques were employed, utilizing established pre-trained models such as ResNet50, Xception, InceptionV3, VGG19, VGG16, and MobileNetV3Small. These models were applied to differentiate between the two species using raw images captured by a smartphone under uncontrolled conditions. The core architecture of the pre-trained models remained unchanged, except for the removal of the final fully connected layer. Instead, a global average pooling layer and two dense layers were appended at the end, comprising 1024 units and by a single unit, respectively. To mitigate overfitting concerns, early stopping was implemented. The results revealed that, among the models assessed, the Xception model exhibited the most promising predictive performance. It achieved the highest average accuracy levels of 0.849 and 0.754 during training and validation, surpassing the other models. Furthermore, fine-tuning the Xception model by extending the number of epochs yielded more impressive outcomes. After 30 epochs of fine-tuning, the Xception model demonstrated optimal performance, reaching an accuracy of 0.843 and displaying a 11.508% improvement in predictions compared to the model without fine-tuning. These findings highlight the efficacy of transfer learning, particularly with the Xception model, in accurately distinguishing visually similar aquatic species using smartphone-captured images, even in uncontrolled conditions.

5-Year-Old Children Performing Piaget’s Liquid Conservation Tasks Demonstrated in Physical and Digital Environment

This study investigates the understanding of Piaget's concept of liquid conservation in 5-year-old children, comparing physical and digital environments of executing conservation tasks. Involving 86 participants (equal gender representation), it employs an Android tablet to demonstrate the pouring of water between glasses with animated images in a digital environment condition and real glasses (one short-wide and one long-narrow) filled with water for the physical environment condition. Each child completed four distinct conservation tasks, each one 3 times, designed to parallel each other in both environments. Two of the tasks concerned the general concept of conservation, and the other two were either about identity or compensation or reversibility concepts. The study aims to determine whether digital environments can be as effective as physical ones in teaching fundamental conservation concepts, exploring the impact of emerging digital learning tools versus traditional methods. Another objective of this study is to find associations between the general concept of conservation and the three other concepts: identity, compensation, and reversibility. This research contributes to the understanding of cognitive development in children and the efficacy of digital versus physical learning aids by verifying that children perceive physical and virtual learning with the same effectiveness.

DEEP LEARNING IN ANIMAL CLASSIFICATION SYSTEM

In this work, we propose a method for the classification of animal in images. Initially, a region merging segmentation method is used to perform segmentation in order to eliminate the background from the given image. From segmented animal images, the shape, texture and color features are extracted. Deep learning with Convolution Network and Support vector is considered for classification. To corroborate the efficacy of the proposed method, an experiment was conducted on our own data set of 30 classes of animals, which consisted of 600 sample images. The experiment was conducted by picking images randomly from the database to study the effect of classification accuracy, and the results show that the Deep Learning classifier achieves good performance.

Too anthropomorphized to keep distance: The role of social psychological distance on meat inclinations

Keeping a distance from food animals helps alleviate moral conflicts associated with meat consumption. Prior research on the ‘meat paradox’ has shown that physical distance from animals reduces negative emotional responses when consuming meat. However, even with physical distance, the presence of animals in meat advertisements and packaging can establish psychological contact. The impact of psychological distance on meat consumption and purchase inclinations has not been well explored. Through four experiments, we discovered that animal anthropomorphism psychologically brings consumers closer to food animals, resulting in reduced intentions to consume and purchase meat. Anthropomorphized animal images notably reduced social psychological distance for consumers with moderate to high (vs. lower) levels of anthropomorphic tendencies. Furthermore, the effect of anthropomorphism was influenced by moral self-efficacy. Specifically, when social psychological distance was reduced, consumers with higher (vs. lower) moral self-efficacy exhibited a significant decrease in their willingness to consume and purchase meat. These findings expand our understanding of the role of anthropomorphism in meat marketing, its limitations, and offer insights for sales strategies. Additionally, the research could inform public health policies on meat consumption, addressing environmental and ethical concerns tied to meat production amid growing worries about animal welfare.

Ion Creangă’s creation in the vision of director Ion Popescu-Gopo

The Romanian director Ion Popescu-Gopo (1923-1989) remained in the history of world cinema as the creator of the Little Man, which became his brand in the field of animation. But his creation is rich enough, including not only animated films, but also fiction films. He is the only director, who in the years ‘60-’80 dared to interpret the stories of the classic of our literature Ion Creangă, starting with The Story of Harap Alb (The White Moor, 1965), The Story of the Pig,(The Story of Love, 1976), The Old Man’s Daughter and the Old Woman’s Daughterl (Maria, Mirabela, 1982),The Bag with Two Coins (The Wager, 1984). The director re-reads the writer’s stories from a modern cinematic perspective, experimenting not only with the ideational message, but also with the production techniques, combining the actors’ play with animated images (Maria, Mirabela or The Wager).