Art Design Research Articles

Aesthetic principles of expressionism in modern architecture

The purpose of the article is to study the aesthetic principles of expressionism that influenced the development of modern architecture. An analysis of the concepts and means of artistic expression of the direction under study is proposed. The conditions for the emergence and formation of expressionism, its artistic methods of expression from conventionally realistic to abstract, as well as the manifestation of this direction of art in architectural design are considered. A brief analysis of the connection between expressionism and other parallel trends or movements of art of the twentieth century is given. Variations of expressionism from the standpoint of abstract art are identified, where the search for interactivity between the artist and the viewer in the process of visual perception of the painting is indicated. It is concluded that imagination is one of the main ways of artistic thinking in the process of author’s artistic design. The manifestation of the aesthetic principles of expressionism in the architecture of individual countries is considered. It has been revealed that expressionism in architecture is characterized by a departure from traditional forms in order to achieve the maximum emotional impact on the recipient. The study of the stated topic allows us to draw a conclusion about the relevance of expressionism at the beginning of the 21st century, which, with its traditions, continues the achievements of expressionism of the 20th century. and at the same time gives a new impetus to artistic expressions of the personal views of artists and architects on the ongoing processes in society. Parallels of the beginning of the 20th – beginning of the 21st centuries. revealed similarities in the aesthetic principles of the formation of the subject-spatial architectural environment. Expressionist techniques, means and methods of working on a painting or object are most accurately able to express the feelings of artists and architects, their psychological stress, the conviction that the viewer must go through a new experience while looking at an architectural or artistic work.

Exploring the Integration of Multimodal Data and CAD Collaborative Design Technology in Art Design

Exploring the Integration of Multimodal Data and CAD Collaborative Design Technology in Art Design

Connection between the artistic design of form in architecture and design and laws of psychology and physiology of perception

Specialists who have ever been involved in compositional work could not help but notice that there is a connection between compositional methods and techniques (architects, designers and artists use them in their work) and the fundamental tools of perception that nature has endowed man with and which he uses. The direction of Gestalt psychology is of greatest importance for the chosen topic. This direction describes and studies integral structures that, in principle, cannot be derived from the components that form them. At the same time, the theory of composition studies such laws of construction of a work of art that ensure the integrity of this work. It is quite obvious that the process of creating an attractive form simply must be built according to the laws of perception that are laid down by nature. It is this interesting connection that this article is devoted to.

Modern environmental art design based on Artificial Intelligence technology and ecological civilization

This study delves into a novel approach for energy conservation and environmental pollution reduction through modern environmental art design, guided by the ecological civilization concept and powered by artificial intelligence (AI) technology. The environmental art framework, aligning with the ecological civilization paradigm, is intricately designed. The data acquisition layer employs diverse sensors to gather equipment status, environmental, and pollution data, transmitting it to the executive controller layer via internal WIFI connectivity. The collected data undergoes meticulous analysis and processing within the data layer before reaching the actuator control layer. Leveraging support vector machines in artificial intelligence, the executive controller layer amalgamates the analyzed equipment and environmental data to devise energy-saving equipment and environmental pollution control schemes. Real-time visualization of these outcomes is achieved through the display operation layer. Findings affirm the effectiveness of this method in acquiring pertinent data for modern environmental art design and managing equipment states. Implementation of this approach successfully diminishes power consumption, dust concentration, and formaldehyde levels in the modern environmental art design zone, showcasing its prowess in energy conservation and pollution control. The integration of AI within the ecological civilization framework highlights its potential in fostering sustainable and environmentally conscious practices in modern art creation.

Emotional Expression of AI-generated Artistic Design: A Case Analysis Approach

Emotional Expression of AI-generated Artistic Design: A Case Analysis Approach

Construction and application of interactive platform of art design based on multimedia technology

Contemporary art design not only pursues the quality of the work itself, but also pays attention to the sensory aspects of people’s needs for art design. Traditional art design methods can be limited by time, space and other objective conditions, and often fail to achieve the designer’s expected effect, and visitors’ experience is not strong. The usage of multimedia technology in art and design can enrich its expression and enhance visitors’ experience. In order to increase the sense of interaction between the platform and users, multimedia technology is incorporated into the interactive art design platform generated by VR technology in this paper. This article combines multimedia technology with interactive technology to construct an interactive platform for art and design, and applies it to the display of Dunhuang murals. Through the analysis of user experience feedback, the effectiveness of art and design display and interaction is verified. Display and interact with Dunhuang murals as interactive platform applications. This test is to extract women’s clothing colors from the same tradition in different times in the color extraction exploration module of the interactive platform, so as to provide accurate information for displaying women’s clothing color changes and comparing interactions. The findings show that the platform is capable of extracting and recognizing the color characteristics of the murals, accurately identifying user signals, and noticing 3D modeling of images via VR technology. This capability provides solid technical and data support for the platform’s interaction module. The interaction design, platform functionality, and layout can support the majority of users in terms of cognition, perception, and interaction, pique their interest, and enhance their experience, according to evaluation of trial user information. The interaction ends abruptly, according to a small percentage of users, and they had a bad experience overall.

Application of Using Improved Genetic Algorithm in Art Design

Art design encompasses the creative process of conceptualizing and crafting visual and aesthetic elements to convey messages, evoke emotions, and stimulate thought. It involves the deliberate selection and arrangement of colors, shapes, textures, and forms to create meaningful and impactful compositions across various mediums such as painting, sculpture, graphic design, and multimedia. This paper proposes an innovative approach to enhance art design through the application of an improved genetic algorithm (GA) coupled with Statistical Spider Swarm Optimization (SS-O). By integrating GA's evolutionary principles with the adaptive capabilities of SS-O, the proposed framework aims to optimize the generation of artistic compositions across various media. Through a series of experiments and simulations, the effectiveness of the hybrid algorithm is evaluated in terms of its ability to generate aesthetically pleasing designs while balancing artistic diversity and coherence. The improved GA component facilitates the exploration of diverse design solutions, while SS-O provides dynamic optimization capabilities by leveraging statistical analysis of swarm behavior. Simulation results demonstrate the efficacy of the approach, with generated designs achieving fitness scores ranging from 0.88 to 0.95, indicative of high aesthetic appeal. Moreover, the diversity index values ranging from 0.75 to 0.82 underscore the algorithm's ability to produce a varied range of artistic compositions. These numerical outcomes signify the potential of the proposed approach to revolutionize the creative process in art and design domains, offering new avenues for generating captivating visual expressions.

Cloud Based Ccmc Model for Application of Genetic Algorithm Based on Cloud Computing in Art Product Design

Art design has entered a new era with the integration of cloud computing technology, revolutionizing the creative process and expanding artistic possibilities. By leveraging the vast computational power and storage capabilities of cloud platforms, artists can explore innovative techniques, collaborate with peers remotely, and access a wealth of digital resources from anywhere in the world. Cloud computing enables artists to work with large-scale datasets, create complex visualizations, and render high-resolution artworks with ease. Moreover, cloud-based tools and applications offer flexibility and scalability, allowing artists to experiment freely and iterate rapidly. Whether creating digital paintings, 3D animations, or interactive installations, cloud computing empowers artists to push the boundaries of their creativity and bring their visions to life in ways previously unimaginable. This paper presents an innovative application of genetic algorithm (GA) leveraging cloud computing technology for art product design, with a focus on the Centralized Clustering Middle Chain (CCMC) framework. By harnessing the computational power and scalability of cloud platforms, GA facilitates the optimization of design parameters to generate novel and aesthetically pleasing art products. The CCMC framework streamlines the design process by centralizing data clustering and analysis, enabling efficient exploration of design space and identification of optimal solutions. Through simulated experiments and empirical evaluations, the effectiveness of the GA-based approach in art product design is assessed. Results demonstrate significant improvements in design quality and efficiency, with the GA-enabled cloud computing solution achieving a 40% reduction in design iteration time and a 30% increase in product innovation compared to traditional methods.

Immersive Multimedia Art Design Based on Deep Learning Intelligent Vr Technology

Virtual Reality (VR) based art design offers a revolutionary platform for artists to explore new dimensions of creativity and expression. By immersing users in virtual environments, VR art transcends traditional limitations, enabling the creation of immersive and interactive experiences that defy conventional boundaries. Artists harness VR technology to sculpt three-dimensional forms, paint in volumetric space, and manipulate light and sound in ways previously unimaginable. Moreover, VR facilitates collaboration and audience engagement, allowing viewers to interact with and even become part of the artwork. From virtual exhibitions to immersive installations, VR art opens up endless possibilities for artistic innovation and audience participation. This paper introduces an innovative approach to immersive multimedia art design, leveraging deep learning intelligent Virtual Reality (VR) technology alongside Centralized Data Transmission Classification (CDTC) with the integration of IoT multimedia sensor data. By combining these advanced technologies, artists can create captivating and dynamic multimedia experiences that engage multiple senses and transcend traditional artistic boundaries. Deep learning algorithms analyze and interpret vast amounts of sensory data collected from IoT multimedia sensors, enabling the generation of immersive VR environments that respond intelligently to user interactions. CDTC facilitates efficient data transmission and classification, optimizing the integration of real-time sensor data into the VR experience. Through a series of experiments and simulations, the efficacy of the proposed framework is demonstrated, showcasing its ability to create immersive art installations that dynamically adapt to user input and environmental stimuli. in a simulated VR environment, deep learning algorithms processed IoT sensor data in real-time, resulting in an average classification accuracy of 92% for environmental stimuli recognition. Additionally, CDTC facilitated efficient data transmission, reducing latency by 30% compared to traditional methods.

Computer Aided Decorative Art Design and Multimedia Dynamic Display Based on Deep Learning Model

Computer Aided Decorative Art Design and Multimedia Dynamic Display Based on Deep Learning Model

Intelligent Optimization Using Multi-objective Genetic Algorithms in New Media Art Design

Intelligent Optimization Using Multi-objective Genetic Algorithms in New Media Art Design

Contested spaces as spectacles

ABSTRACT This article discusses the role of scenographic methodologies in revisiting spaces associated with political conflict and trauma. In doing so, the author presents her artistic research and design process behind the art installation ‘Spectators in a Ghost City’, the exhibition of the Cyprus National participation in the Prague Quadrennial of Performance Design and Space 2023 which places the occupied city of Famagusta, abandoned since 1974, as a contested-space-becoming-spectacle. The author describes how analysing the space through a scenographic lens allows a close examination of the city’s materiality and how this, in turn, becomes the source for artistic creation. Focusing on the scenographic process of scaling down, sculptural maquettes and portable models in walking practices are approached as symbolic objects for communicating issues on displacement, space politics, surveillance and agency. In that sense, scenographic methodologies are discussed as thinking processes, a political act of resistance, and a tool for negotiating artistic practices and real spaces of conflict. This process is defined as ‘scenography reversed’, where a real place becomes a dramatised scene, allowing alternative understandings that expand beyond hegemonic narratives. The article places Famagusta as a paradigm of contested spaces and questions whether scenographic methodologies can be a possible approach to reconciliation and conflict resolution.

Discussion on the Application of Artificial Intelligence Image Generation Technology in Art Design

With the continuous development of artificial intelligence technology, the application of image generation technology in the field of art and design has become more and more extensive. This paper mainly discusses the application of image generation technology integrating artificial intelligence in art design, and analyzes the potential application of artificial intelligence technology in art design, including automatic creation, art style conversion and art generation. In terms of automated creation, artificial intelligence technology can generate new works with artistic characteristics by learning a large number of artistic works. By adjusting the parameters and inputs of the model, works with different styles and themes can be generated, providing more creative inspiration and possibilities for the artist. It provides artists with more creative ways and possibilities. In general, the application of image generation technology integrating artificial intelligence in art design has broad development prospects and potential, bringing more choices and possibilities for the art market, and promoting the application and development of artificial intelligence technology in the field of art and design.

Assessing the Ignored Potential: Employing and Assessing Art Design Installations to Revitalize Islamabad's Urban Open Spaces

Assessing the Ignored Potential: Employing and Assessing Art Design Installations to Revitalize Islamabad's Urban Open Spaces

Research on Art Design Curriculum from the Perspective of Ideological and Political Curriculum Take illustration design as an example

This paper combines illustration design with the ideological and political course, discusses the reform ideas of integrating ideological and political course into illustration design from three aspects of the necessity of curriculum reform, theoretical basis and practical exploration, and puts forward the educational path and methods of art design professional courses.

Sonic branding: A narrative review at the intersection of art and science

AbstractThe field of sonic branding/marketing has grown rapidly in recent years, as has commercial interest in more science‐based approaches to the practice, particularly as more brands and agencies look for qualitative and quantitative evidence to support the efficacy of sonic branding. In this research note, we explore the ways in which the design and execution (i.e., the “art”) of sonic branding initiatives can be informed by overlapping approaches and techniques drawn from the sciences, namely psychoacoustics, semiotics, music/auditory cognition, and crossmodal research. We explore whether the rapid growth of generative AI may represent the next major evolution in the design, creation, and assessment of sonic assets, where science and art are used to train AI tools that could one day augment (and potentially disrupt) the work of human sound designers and composers. These developments notwithstanding, it is argued that sonic branding will likely remain as much an art as a science, though basing one's approach on the emerging scientific literature ought to at least tilt the odds of success in the creative's favor.

Ancient Chinese painting style transfer based on CycleGAN

Style transfer aims to alter the visual aesthetic of images by giving them a different artistic style. With the rapid advancement of deep learning, style transfer tasks have made significant progress, introducing new perspectives and innovative potentials within the realm of image processing. This study seeks to explore style transfer methods based on Cycle-Consistent Adversarial Networks (CycleGAN), enabling contemporary landscape photographs to take on the form of ancient Chinese paintings. This endeavor opens up fresh possibilities for artistic creation, image editing and design applications. The research encompasses an exposition of the process involved in constructing the CycleGAN model, alongside presenting research findings. Furthermore, it delves into the discussion of crucial techniques employed during the model training process, specifically the utilization of cycle consistency loss in configuring the loss functions. Lastly, this study ventures into future research directions, including strategies for further enhancing the performance and expanding the application scope of this style transfer model.

The recurring collocation of vreiðr and vega in Old Norse poetry

Poetry in early Germanic vernaculars exhibits variations on a metrical form predicated on a pattern of alliterating stressed syllables linking two halves of a line (in contrast to syllabic metres in which scansion requires a fixed number of syllables per line). This gave rise to the phenomenon of recurring alliterative collocations: the repeated combination of alliterating words or word-roots within a given poetic corpus. It is likely that such collocations originated, like formulae in oral-formulaic theory developed by Milman Parry and A.B. Lord, as building blocks for extempore composition during performance. However, there is strong evidence that Old Norse poetry was composed deliberatively and memorized for performance. Recurring collocations in Old Norse verse therefore reflect conscious artistic design rather than compositional expediency. This article focuses on one such collocation—the adjective vreiðr (angry) and the verb vega (to fight, to strike)—as a case study of the way in which composers of Old Norse eddic verse exploited the traditional resonances of certain collocations to shape audience understanding of character and plot.

Composition Color Space: Three Key Words in Art Design

As found in the practice of arts, which is the same as of sciences, a design without imagination is like the water running from nowhere and trees without roots, deprived of vitality and artistic appeal. As illustrated in the old saying that a thousand li journey is started by taking the first step, the three compositions work as both the foundation of art design and provider of unlimited imagination and creativity for urban design and city planning.

Visual resource extraction and artistic communication model design based on improved CycleGAN algorithm.

Through the application of computer vision and deep learning methodologies, real-time style transfer of images becomes achievable. This process involves the fusion of diverse artistic elements into a single image, resulting in the creation of innovative pieces of art. This article centers its focus on image style transfer within the realm of art education and introduces an ATT-CycleGAN model enriched with an attention mechanism to enhance the quality and precision of style conversion. The framework enhances the generators within CycleGAN. At first, images undergo encoder downsampling before entering the intermediate transformation model. In this intermediate transformation model, feature maps are acquired through four encoding residual blocks, which are subsequently input into an attention module. Channel attention is incorporated through multi-weight optimization achieved via global max-pooling and global average-pooling techniques. During the model's training process, transfer learning techniques are employed to improve model parameter initialization, enhancing training efficiency. Experimental results demonstrate the superior performance of the proposed model in image style transfer across various categories. In comparison to the traditional CycleGAN model, it exhibits a notable increase in structural similarity index measure (SSIM) and peak signal-to-noise ratio (PSNR) metrics. Specifically, on the Places365 and selfi2anime datasets, compared with the traditional CycleGAN model, SSIM is increased by 3.19% and 1.31% respectively, and PSNR is increased by 10.16% and 5.02% respectively. These findings provide valuable algorithmic support and crucial references for future research in the fields of art education, image segmentation, and style transfer.