Images for Instruction: A Multilingual Illustrated Dictionary in Fifteenth-Century Sultanate India

This article focuses on the Miftāḥ al-Fużalāʾ (Key of the Learned) of Muhammad ibn Muhammad Daʾud Shadiyabadi (ca. 1490). The Miftāḥ is an illustrated dictionary made in the central Indian sultanate of Malwa, based in Mandu. Although the Miftāḥ’s only illustrated copy (British Library Or 3299) contains quadruple the number of illustrations as Mandu’s famed Niʿmatnāmah (Book of Delights) and is a unicum within the arts of the Islamicate and South Asian book, it has received minimal scholarly attention. The definitions in this manuscript encompass nearly every facet of Indo-Islamicate art history. The Miftāḥ provides a vocabulary for subjects including textiles, metalwork, jewelry, arms and armor, architecture, and musical instruments. The information transmitted by the Miftāḥ is not limited to the Persian, Hindavi, Turki, and Arabic language of the text, but also includes the visual knowledge depicted in paintings. Through an analysis of this manuscript as a whole, this study proposes that the Miftāḥ’s manuscript was an object of instruction for younger members of society and utilizes wonder as a didactic tool.

What Does a Language-And-Vision Transformer See: The Impact of Semantic Information on Visual Representations

Neural networks have proven to be very successful in automatically capturing the composition of language and different structures across a range of multi-modal tasks. Thus, an important question to investigate is how neural networks learn and organise such structures. Numerous studies have examined the knowledge captured by language models (LSTMs, transformers) and vision architectures (CNNs, vision transformers) for respective uni-modal tasks. However, very few have explored what structures are acquired by multi-modal transformers where linguistic and visual features are combined. It is critical to understand the representations learned by each modality, their respective interplay, and the task’s effect on these representations in large-scale architectures. In this paper, we take a multi-modal transformer trained for image captioning and examine the structure of the self-attention patterns extracted from the visual stream. Our results indicate that the information about different relations between objects in the visual stream is hierarchical and varies from local to a global object-level understanding of the image. In particular, while visual representations in the first layers encode the knowledge of relations between semantically similar object detections, often constituting neighbouring objects, deeper layers expand their attention across more distant objects and learn global relations between them. We also show that globally attended objects in deeper layers can be linked with entities described in image descriptions, indicating a critical finding - the indirect effect of language on visual representations. In addition, we highlight how object-based input representations affect the structure of learned visual knowledge and guide the model towards more accurate image descriptions. A parallel question that we investigate is whether the insights from cognitive science echo the structure of representations that the current neural architecture learns. The proposed analysis of the inner workings of multi-modal transformers can be used to better understand and improve on such problems as pre-training of large-scale multi-modal architectures, multi-modal information fusion and probing of attention weights. In general, we contribute to the explainable multi-modal natural language processing and currently shallow understanding of how the input representations and the structure of the multi-modal transformer affect visual representations.

Emerging evolution trends of application of natural products in Alzheimer’s disease

The main objective of this review was to explore the research foci and emerging trends of application of natural products in AD from 1990 to 2019 and evaluated publications qualitatively and quantitatively. CiteSpace V. 4.0 was used to identify top authors, journals, institutions, countries, keywords, co-cited articles, and trends and obtain the visual knowledge maps. Results revealed that the USA, People’s Republic of China and India were the major research countries in this field, while the Western Europe and North America were the areas with frequent international cooperation. Moreover, there was a close collaboration between universities and research institutes. The J Alzheimers Dis was the most productive journal. Alzheimers disease, natural product, brain, central nervous system, disease, and oxidative stress are some of the high centrality and high frequency keywords in the co-occurrence analysis; Indicating Alzheimers disease and its pathogenesis and natural product remain the hotspots in the field. This paper provides an insight into the application of natural products in AD, and provides useful information for AD researchers to find potential collaborators and cooperative institutions.

FORMATION OF AESTHETIC TASTES OF JUNIOR SCHOOLCHILDREN IN ART LESSONS

The article reveals the peculiarities of the formation of aesthetic tastes of junior schoolchildren in art lessons. The content and tasks of artistic and aesthetic development of students are determined by the categories of aesthetic culture, in particular the formation of aesthetic tastes, knowledge, needs, ideals, feelings, development of creative abilities, artistic and aesthetic skills. It was found that the creative nature of the process of formation of aesthetic tastes in the study of art, during art activities as part of the diverse development of personality, requires pedagogical conditions: an acquaintance of junior students with aesthetic, artistic and social content of art as an object of aesthetic tastes; mastering visual knowledge, practical skills and abilities in various types of art activities; use of non-traditional techniques and materials for mastering visual arts; creating a favourable, emotionally rich, humane learning environment in the classroom.The article also highlights the importance of artistic activity in the formation of aesthetic tastes of children of primary school age. During the creation of a certain image or product, students develop artistic taste, observation, creativity, aesthetic perception. In the process of artistic activity, children have the opportunity to embody in works their emotional state, their attitude to the surrounding reality, learn to create the beauty of the world, to notice it in life and in works of fine arts.It is claimed by the author that for the development of imagination, fantasy, creative activity of students, mastering certain knowledge and skills, ability to think, fantasize, it is advisable to use non-traditional drawing techniques that demonstrate an unusual, original combination of materials and tools. Keywords: aesthetic education; aesthetic tastes; art lesson; junior schoolchildren; art activities; pedagogical conditions; means of art; non-traditional drawing techniques.

The value of system dynamics' diagrams for business model innovation

PurposeSystem dynamics (SD) is emerging as a powerful approach to understand, analyse, simulate and predict complex and dynamic business processes. In particular, it is true in the process of business model innovation (BMI) and not only as a computational approach. Due to the visual and diagrammatic tools employed by SD, innovation managers overcome humans' mental limitations and improve knowledge management in the BMI. This paper discloses the value of SD's visual tools, i.e. causal loop diagrams and stock and flow diagrams, to contribute to the “Knowldege Visualization” research line, and promote the application of SD as a powerful approach to support decisions in BMI.Design/methodology/approachGiven the explorative nature and the “how” question driving the research, the methodology involved is a single, holistic case study. In particular, the case is about a business model (BM) diversification, in which an information and communication technology service provider has added to its existing business model a new BM based on a digital multi-sided platform, for passengers transportation.FindingsThe diagrammatic tools of SD, that is causal loop diagrams and stock and flow diagrams, allowed entrepreneurs to overcome the complexity of the business parameters concurring in the design of the BM.Originality/valueThe value of this research is in the exploratory approach and in the originality of the perspective by which SD is analysed: the visual knowledge perspective.

Toward Computer Aided Visual Analogy Support (CAVAS): Augment Designers Through Deep Learning

The goal of this research is to develop a computer-aided visual analogy support (CAVAS) framework that can augment designers’ visual analogical thinking by providing relevant visual cues or sketches from a variety of categories and stimulating the designer to make more and better visual analogies at the ideation stage of design. The challenges of this research include what roles a computer tool should play in facilitating visual analogy of designers, what the relevant and meaningful visual analogies are at the sketching stage of design, and how the computer can capture such meaningful visual knowledge from various categories through analyzing the sketches drawn by the designers. A visual analogy support framework and a deep clustering model, called Cavas-DL, are proposed to learn a latent space of sketches that can reveal the shape patterns for multiple categories of sketches and at the same time cluster the sketches to preserve and provide category information as part of visual cues. The latent space learned serves as a visual information representation that captures the learned shape features from multiple sketch categories. The distance- and overlap-based similarities are introduced and analyzed to identify long- and short-distance analogies. Extensive evaluations of the performance of our proposed methods are carried out with different configurations, and the visual presentations of the potential analogical cues are explored. The evaluation results and the visual organizations of information have demonstrated the potential of the usefulness of the Cavas-DL model.

The First of All Natural Sciences: Roger Bacon on Perspectiva and Human Knowledge

This article is devoted to Roger Bacon’s understanding of perspectiva as “the first of all natural sciences.” After considering a few alternative medieval definitions and classifications of this discipline – such as al-Fārābī’s, Grosseteste’s and Kilwardby’s – the author turns to Bacon’s arguments for according to perspectiva so exceptional a role. He shows that Bacon’s arguments are grounded in his peculiar understanding of the visual process: according to Bacon, vision is indeed the only sense in which perception takes place “by reasoning” (per sillogismum). The author argues that this theory of perception also lays the foundations for Bacon’s – prima facie amiss – claim that “concerning vision alone, and no other sense, have philosophers developed a separate science.” The author explores this point by contrasting with one another Bacon’s conception of perspectiva and of music, and closes with some more general remarks on the implications of Bacon’s account of the visual process for his theory of knowledge. Based on his theory of a “vision by reasoning,” the author concludes that Bacon came to reinterpret perspectiva as the organon of visual knowledge.