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Graphic design, as a product of the burgeoning new media era, has seen its users' requirements for images continuously evolve. However, external factors such as light and noise often cause graphic design images to become distorted during acquisition. To enhance the definition of these images, this paper introduces a novel image enhancement model based on visual features. Initially, a histogram equalization (HE) algorithm is applied to enhance the graphic design images. Subsequently, image feature extraction is performed using a dual-flow network comprising convolutional neural network (CNN) and Transformer architectures. The CNN employs a residual dense block (RDB) to embed spatial local structure information with varying receptive fields. An improved attention mechanism module, attention feature fusion (AFF), is then introduced to integrate the image features extracted from the dual-flow network. Finally, through image perception quality guided adversarial learning, the model adjusts the initial enhanced image's color and recovers more details. Experimental results demonstrate that the proposed algorithm model achieves enhancement effects exceeding 90% on two large image datasets, which represents a 5%–10% improvement over other models. Furthermore, the algorithm exhibits superior performance in terms of peak signal-to-noise ratio (PSNR) and structural similarity index measure (SSIM) image quality evaluation metrics. Our findings indicate that the fusion model significantly enhances image quality, thereby advancing the field of graphic design and showcasing its potential in cultural and creative product design. [ABSTRACT FROM AUTHOR]

To enhance the segmentation accuracy of car front face elements such as headlights and grilles for car front face design, and to improve the superiority and efficiency of solutions in automotive partial modification design, this paper introduces MD-TransUNet, a semantic segmentation network based on the TransUNet model. MD-TransUNet integrates multi-scale attention gates and dynamic-channel graph convolution networks to enhance image restoration across various design drawings. To improve accuracy and detail retention in segmenting automotive front face elements, dynamic-channel graph convolution networks model global channel relationships between contextual sequences, thereby enhancing the Transformer's channel encoding capabilities. Additionally, a multi-scale attention-based decoder structure is employed to restore feature map dimensions, mitigating the loss of detail in the local feature encoding by the Transformer. Experimental results demonstrate that the MSAG module significantly enhances the model's ability to capture details, while the DCGCN module improves the segmentation accuracy of the shapes and edges of headlights and grilles. The MD-TransUNet model outperforms existing models on the automotive front face dataset, achieving mF-score, mIoU, and OA metrics of 95.81%, 92.08%, and 98.86%, respectively. Consequently, the MD-TransUNet model increases the precision of automotive front face element segmentation and achieves a more advanced and efficient approach to partial modification design. [ABSTRACT FROM AUTHOR]

Scene-based image semantic extraction and its precise sentiment expression significantly enhance artistic design. To address the incongruity between image features and sentiment features caused by non-bilinear pooling, this study introduces a generative adversarial network (GAN) model that integrates visual relationships with sentiment semantics. The GAN-based regularizer is utilized during training to incorporate target information derived from the contextual information into the process. This regularization mechanism imposes stronger penalties for inaccuracies in subject-object type predictions and integrates a sentiment corpus to generate more human-like descriptive statements. The capsule network is employed to reconstruct sentences and predict probabilities in the discriminator. To preserve crucial focal points in feature extraction, the Convolutional Block Attention Mechanism (CBAM) is introduced. Furthermore, two bidirectional long short-term memory (LSTM) modules are used to model both target and relational contexts, thereby refining target labels and inter-target relationships. Experimental results highlight the model's superiority over comparative models in terms of accuracy, BiLingual Evaluation Understudy (BLEU) score, and text preservation rate. The proposed model achieves an accuracy of 95.40% and the highest BLEU score of 16.79, effectively capturing both the label content and the emotional nuances within the image. [ABSTRACT FROM AUTHOR]

Optical processing technology can improve the accuracy and efficiency of image processing. Visual packaging art design simulation is to quickly generate realistic packaging effects in the early stage of packaging design, so as to make better design decisions. Traditional simulation methods often require a lot of time and human resources, and the results lack realism and detail. Machine vision technology based on optical processing can make full use of image processing algorithms and computer vision technology to achieve efficient and accurate packaging design simulation. In this paper, a machine vision technology framework based on image optical processing is proposed. In the image acquisition stage, high-resolution cameras are used to acquire real packaging images, and in the optical processing stage, algorithms are used to enhance, reduce noise and correct images to improve image quality and clarity. In the image analysis stage, machine learning algorithms are used to extract features and detect and identify packaging elements, providing data support for subsequent simulation rendering. The results show that the machine vision technology based on image optical processing can generate high quality and realistic simulation effect of packaging design. Compared with traditional methods, this technique has achieved significant improvements in terms of time cost and design quality. [ABSTRACT FROM AUTHOR]

Art design is a method of conveying human feelings and emotions, particularly via the use of visual structures such as paintings or sketches. Every element of our life, including arts and crafts, has been positively affected by the introduction of novel technologies such as artificial intelligence (AI) and machine learning (ML). In today's modern environment, these technologies have altered the techniques of art creation, consumption, and distribution. In today's environment, ML and human emotions are the two most important aspects for interactive and high‐quality art design. Whereas traditional learning systems can be extremely effective in the teaching and learning process of art‐related subjects, AI and ML can be very effective in the teaching and learning process of art‐related subjects for the advancement of learners' artistic skills. The productive and active role of AI and ML in the developments and advancements of art design has been given a very comprehensive and detailed overview in this study. Following a detailed examination of the existing techniques, distinct characteristics have been identified. Six of the most widely utilized features were chosen from the literature to execute the analytical hierarchy process (AHP). For ranking the options based on the weights derived by AHP, the TOPSIS algorithm is used. The option with the best performance came in first, whereas the one with the worst performance came in last. [ABSTRACT FROM AUTHOR]

The mental model of art design in the realm of virtual reality (VR) technology is a dynamic fusion of creativity, immersion, and technological innovation. In this paradigm, artists leverage the immersive capabilities of VR to transcend traditional boundaries, creating a multisensory experience that goes beyond the confines of a two-dimensional canvas. The artist's mental canvas extends into a threedimensional space where users can engage with art on a profound level, exploring and interacting with the artwork in ways previously unimaginable. The core objective is to redefine art design design through the lens of machine vision cognition into the ethical and social implications inherent in Art Design. With the integration of Hidden Markov Probabilistic Swarm Optimization (HMPSO) to amplify the capabilities of VR systems. At the forefront of this study is the reimagination of art design design, characterized by aesthetics, ergonomics, and functionality. The infusion of machine vision cognition into these designs not only enhances user experience but also prompts contemplation of ethical considerations surrounding privacy, accessibility, and informed consent. Ethical and social implications are scrutinized comprehensively, acknowledging the profound impact of VRs on individual rights, security, and privacy. The research probes into equitable access to VR technologies, ethical data utilization in art design, identity verification, and surveillance contexts. Central to this multidisciplinary inquiry is the integration of Hidden Markov Probabilistic Swarm Optimization (HMPSO). With swarm intelligence and probabilistic modelling, HMPSO enhances the efficiency, accuracy, and reliability of Mental Model VR systems. It addresses the critical challenge of reducing false positives and false negatives in VR authentication. The research methodology comprises performance evaluations, ethical analyses, and socio-cultural investigations, offering a comprehensive view of the interplay between design innovation, machine vision cognition, ethical awareness, and the application of HMPSO in the Art Design. [ABSTRACT FROM AUTHOR]

Under the background of the continuous impact of new media, with the deepening of art education reform, more creative teaching thinking and teaching methods are integrated into the art design education classroom in universities. In the continuous progress of art design major, how to change the traditional art education classroom and make the teaching more innovative has become one of the research contents that the teaching workers focus on. Therefore, in order to export interdisciplinary talents to the society, it is an inevitable trend for universities to act interdisciplinary teaching and learning mode in combination with the background of new engineering and the widely used STEAM concept. This paper analyzes the teaching mode of art design major in higher education, and then analyzes the current situation of engineering practice courses in universities. According to the characteristics of art students and engineering students, it explores the interdisciplinary teaching mode of introducing art design elements into engineering practice courses, which can provide the orderly development of art education with reference in universities. [ABSTRACT FROM AUTHOR]

The rapid advancement of industrialization has sparked the emergence of diverse art and design theories. As a trailblazer in the realm of industrial art and design theory, visual communication has transcended the boundaries of merely arranging and combining individual elements. Embracing the potential of artificial intelligence technology, the extraction of multidimensional abstract data and the acceleration of the art design process have gained considerable momentum. This study delves into the abstract emotional facets within the methodology of visual communication art design. Initially, convolutional neural networks (CNN) are employed to extract expressive features from the poster's visual information. Subsequently, these features are utilized to cluster emotional elements using a variational autoencoder (VAE). Through this clustering process, the poster images are categorized into positive, negative, and neutral classes. Experimental results demonstrate a silhouette coefficient surpassing 0.7, while the system framework exhibits clustering accuracy and efficiency exceeding 80% in single sentiment class testing. These outcomes underscore the efficacy of the proposed CNN-VAE-based clustering framework in analyzing the dynamic content of design elements. This framework presents a novel approach for future art design within the realm of visual communication. [ABSTRACT FROM AUTHOR]

The research expects to promote "artificial intelligence (AI) + Education" and cultivate high-quality art design talents with international perspectives. First, random sampling recruits 100 Art Design sophomores in a university and divides them into a test group and a control group. The Questionnaire Survey (QS) is used to obtain research data, including students' satisfaction with the curriculum, training mode, and innovation environment. Meanwhile, some deficiencies in the traditional educational model are revealed alongside targeted suggestions. Then, a comparative analysis is performed on the design works of the two groups and the student's evaluation of the existing and proposed models. The result proves the effectiveness of the proposed international art design talents-oriented Human–Computer Interaction (HCI)-based training model. The research results imply that students are less satisfied with the existing curriculum, training mode, and innovative environment. About 40% of students hold a neutral attitude towards the current curriculum. They hope that the school provides a more comprehensive and flexible curriculum, personalized training methods, and a relaxed learning environment conducive to creativity. Students in the test and the control groups have gained significant differences in the scores of design works. The test group has scored relatively high, and their works contain more international elements than the control group. Meanwhile, the test group's works reflect a deeper understanding of theoretical knowledge. They give a high evaluation of the proposed talent training model. Thus, the proposed HCI-based new talent training model is effective. Therefore, the proposal is of great significance for promoting the "AI + Education" and talent training models. [ABSTRACT FROM AUTHOR]

After entering the twenty-first century, with the development of science and technology represented by artificial intelligence, the content of art design and creation is increasingly rich. Its intelligence, interactivity and digital content expression make the relationship between science and technology, art and people more close and also bring new opportunities for the development of interactive art. Among them, human–computer interaction is more and more widely used. With the promotion of this kind of technology, interactive art is no longer based on auditory sensory experience, but on the in-depth study of human nature and comprehensive senses. On this basis, human–computer interaction technology is introduced, thus forming a comprehensive visual art form, which communicates and expresses through strong interaction, initiative and emotion. Based on machine learning technology and human–computer visual interaction technology, this paper explores the art visual communication module based on human–computer interaction system. By analyzing the audience's line of sight and visual differences, we can get the audience satisfaction, so as to improve the expression of the work. Firstly, this paper proposes the design of human–computer interaction visual structure and introduces the basic structure of art visual communication system, the simulation of art visual scene, the process and evaluation index of human–computer interaction recognition, visual recognition effect, etc., based on the needs of visual interaction. Finally, it analyzes the common forms of human–computer interaction in art visual communication, the reconstruction of thinking mode of art visual communication and the development direction of art visual communication. This paper believes that human–computer interaction technology plays a leading role in the development of the art field. It has a variety of functions, displays methods and values. By studying machine learning algorithm and human–computer interaction system, this paper applies it to the field of artistic vision, thus promoting the development of artistic visual communication. [ABSTRACT FROM AUTHOR]

With the development of the society, people's material needs are increasing rapidly. Based on this background, intelligent household furniture products with high-tech content are integrated into the field of interior design, and then gradually infiltrated into people's production and life. And from a smart technology perspective, we analyze the art design of smart home products based on machine learning algorithm. This algorithm can make the actual classification results of the test samples consistent with the network output values, and the error values can also meet the accuracy requirements, so as to effectively determine the defect types of the parameter samples. Among them, the art design of smart home products includes home equipment network group, embedded gateway implementation, cloud server construction and interaction design, independent product auxiliary control system and other parts. Finally, through the simulation test results of the intelligent positioning function of the product, we can know that the communication efficiency of the product basically meets the requirements. Interior design products are indispensable in people's home life, and play an important role in the whole indoor environment, such as art paintings, bonsai, woven art, etc. In addition, household appliances and lamps will also affect the aesthetic feeling of the whole interior design. This study tries to introduce machine learning technology in the field of interior art design to make it more intelligent, and a kind of effective algorithm design is completed. [ABSTRACT FROM AUTHOR]

The main purpose of this scientific study is to identify key areas for the development of the artistic and creative activity of students studying the basics of design in higher educational institutions, which contributes to improving their creative abilities and developing the ability to create an innovative product design. The basis of the methodological approach in this scientific study is a combination of methods of systematic analysis of the key principles of teaching design in modern higher educational institutions with a comprehensive study of the real prospects for the introduction of innovative solutions in the process of teaching design in order to develop artistic and creative activity among future specialists in this profession. The results are the importance of developing modern students' artistic and creative activity for design departments of higher educational institutions to improve their skills in creating artistic product design and the ability to develop innovative design were obtained. Also, the results illustrate the success of applying specific methods of training designers to implement the tasks. The practical significance of the results obtained in this research work lies in the possibility of their application in the process of teaching students of design departments of modern higher education institutions to develop their understanding of the principles of artistic design and the ability to transfer such skills to the creation of modern products with innovative design. [ABSTRACT FROM AUTHOR]

Animation ink is a unique form of artistic expression, which is taken from traditional ink painting, and through the continuous exploration and advancement of animators, it has gradually formed its language system and formed a unique artistic style in expression and mood shaping. In this paper, the spatial domain noise reduction method and the transform domain noise reduction method are integrated, and the two types of algorithms complement each other to obtain a better denoising effect. The local pixel block matching algorithm is used to select similar block samples, which makes the covariance calculated by a principal component analysis more accurate in the next step, and then distinguishes the signal from the noise well. The adaptive bilateral filtering algorithm based on residual noise variance estimation uses the spatial proximity and pixel value similarity in the animated ink and wash image under the premise of the optimal set of filtering parameters, and adopts the local weighted average method to obtain the recovered animated ink and wash image. To effectively protect and enhance the detail information such as edges of the animated ink and wash image for animated ink and wash character modeling design. The method in this paper makes full use of the properties between spatial pixels of animated ink and wash images with both rotation invariance and translation invariance. The experimental results on the test database show that the method in this paper can extract features better. The purpose of this paper is to explore how to inherit and bring into play the fine cultural and artistic essence of ink art, to uncover the expressive elements applicable to animation ink character modeling design, and to make them reasonably and effectively used in the creation of animation ink character modeling to maintain the vitality of animation ink character modeling design. [ABSTRACT FROM AUTHOR]

Entrepreneurship education in Chinese colleges and universities began in the early 21st century. After more than 20 years of development, it has reached an unprecedented scale. At present, there are many studies on entrepreneurship education for undergraduates in Chinese colleges and universities, but only a few general studies on entrepreneurship education in higher vocational education. Particularly, the analysis of the status quo of students' entrepreneurship education and the research on the improvement of entrepreneurship education has not yet been widely discussed. This research adopted the semi-structured interview method and used purposive sampling to select 8 students with entrepreneurial willingness in lower grades and 8 in upper grades of higher vocational art and design in the Guangzhou area, as well as 8 students who have succeeded in entrepreneurship after graduation, giving a total of 24 students. The interview was designed based on the concept of Entrepreneurial Thought and Action (ET&A) entrepreneurship education. The interview outline was derived from the three aspects of learning, action, and creation. After the interviews were conducted, coding and qualitative analysis were performed to identify the knowledge and skills required by art students in higher vocational colleges to establish a business, and the problems encountered by successful students in entrepreneurship that might be encountered in the future. Based on the conclusions, the method and content of entrepreneurship education in schools could be improved. In addition, the research results showed that to fulfill the aim of entrepreneurship, art and design students in higher vocational colleges need to learn knowledge and skills such as entrepreneurial courses, professional knowledge, and entrepreneurial skills (competition, training, simulation, practice, etc.). Meanwhile, students who had succeeded in entrepreneurship believed that it was necessary to improve the entrepreneurship education curriculum system, pay attention to entrepreneurship practice teaching, and strengthen the linkage between home, school, and enterprise to promote entrepreneurship learning, thereby enhancing innovation and entrepreneurship ability. [ABSTRACT FROM AUTHOR]

The study aimed to detect phenomenal treatments in the design of indoor spaces for event rooms and joys according to their performance effectiveness. In the light of the realization of changing formal values of the elements across them, the functional and aesthetic expressive aspect is done. In order to enforce the research objective, the researcher conducted a thorough study, which included three chapters, the first dealing with the problem of research and its relevance and purpose, as well as the limits and definition of terminology. Chapter II contained the theoretical framework, which in turn included researchers, the first of which took demonstrational treatments in indoor spaces. Then came the second research aesthetics of demonstrational treatments in indoor spaces and the employment of systems and design relationships, and then came up with a set of conclusions and recommendations. [ABSTRACT FROM AUTHOR]

Art, like language, is a method for expressing a person's thoughts and opinions to others. Art design is a way of conveying human sentiments and emotions, particularly via the use of visual structures such as paintings or drawings. Every element of our lives, including arts and crafts, has been favorably influenced by the introduction of innovative technologies such as artificial intelligence (AI) and deep learning (DL). In today's modern era, the technologies have revolutionized the way art is created, consumed, and distributed. Machine learning and human emotions are the two most important aspects of interactive and high-quality art design. In the teaching and learning of art-related courses, AI and machine learning are used to develop students' creative talents more successfully than traditional learning methods. With the use of information technology, designers build and design more productive artwork in very little time and with much less effort. In the evolution and creation of interactive and intelligent digital art, artificial intelligence and machine learning are playing a highly positive role. Art developed with the use of these approaches is capable of conveying human emotions and sentiments precisely and correctly. The proposed study presents a comprehensive overview of various AI-grounded smart and intelligent applications employed for the betterment and development of art design. The study provided a summary of the existing approaches used in the area of art design for the designing of high-quality and precise artwork. Then, based on the proposed overview, various features are extracted from the existing literature. From these extracted features, important features were selected for the decision-making procedure and ranking. To perform the decision-making process for the ranking of the accessible alternatives, the Graph Theory Matrix Approach was applied. The results of the study show effectiveness of the AI-based systems for art design. [ABSTRACT FROM AUTHOR]

Farmer's Ecological culture is a social ideology, human spirit and social system guided by ecological values; in a broad sense, it is a new way of life for human beings, in which man and nature develop harmoniously. Ecological art design means that, in the process of environmental art design, designers take environmental protection and reducing pollution and waste as their design guiding principles, and take into account the fit between their design results and external nature to avoid excessive transformation and a sense of incongruity, and trying to make their works to achieve the effect of natural integration. This paper introduces the constituent elements and evaluation system of art design of rural environment, conducts the process analysis of art design of rural environment from the perspective of ecological culture, performs the ecological description and visual form analysis of art design of rural environment, proposes the realizing pathways for art design of rural environment from the perspective of ecological culture, expounds the expression methods and process modules of ecological art design of rural environment, and finally takes a village in Yuci District, Jinzhong City, Shanxi Province, Central China as an example, to carry out a case application and its result analysis. The research results show that the art design of rural environment based on the principle of ecological culture can clarify the specific requirements of landscape optimization, arrange the natural balance and social development needs in the configuration of geographical space, and form a landscape network system that maintains the overall natural environment. This in turn expands the concept of rural landscape and environment to a wider field, integrating natural resource protection, rural land use and landscape planning in the entire region. [ABSTRACT FROM AUTHOR]

The purpose of this study was to understand the influence mechanism of college students' entrepreneurial intention in view of the increasing number of college students at present to alleviate college students' employment competition. The psychological factors that influence the entrepreneurial tendency of art graduates were analyzed and studied. First, venture capital and factors affecting entrepreneurial performance were analyzed. Second, the coefficient calculation is carried out for college students majoring in art through the regression analysis of the logistic model. Finally, a team entrepreneurial performance questionnaire was designed, and team reward levels were discussed. The results show that the logistic model can well reflect the real situation of the respondents. The significance level of the entrepreneurial team was 0.02, which was correlated. Additionally, corresponding suggestions were put forward according to the questionnaire results. Clear team goals, assignment of tasks to members, good pressure resistance, and psychological quality of members are necessary qualities for successful entrepreneurship. This conclusion provides a certain theoretical basis for the current college students' entrepreneurial learning and a reliable inspiration for helping college students to successfully start a business. [ABSTRACT FROM AUTHOR]

This paper investigates the art design of user interaction experience in mobile systems through the methods of contextual perception and machine learning. The theoretical foundations for the design of intangible cultural heritage interactive display resources include digital display theory, intangible cultural heritage education theory, embodied cognition theory, and gamification design theory. Based on the modelling and analysis of the theoretical foundations, the design principles are derived, including the heritage education principle, the somatic interaction design principle, and the content design principle. In this paper, we use ontologies to construct user knowledge models, fuse multi-situational similarity metrics, screen out candidate neighbour sets through preliminary screening, then combine the user's activity to construct time-based weight tensor scores, use tensor decomposition to obtain recommendation evaluation values, and finally use the recommendation evaluation values to make artistic recommendations. The experimental results show that the algorithm can still obtain a good recommendation implementation in the case of extremely sparse data. The analysis of the fit between augmented reality and folk art appreciation class, as well as the reference to relevant application cases, make design and practice of augmented reality application in folk art appreciation class, try to solve the common problems in folk art appreciation class, analyse the feedback effect and make a summary and outlook. [ABSTRACT FROM AUTHOR]

Summary: More and more diversified environmental art design, combined with advanced 3‐D virtual virtual reality (VR) technology, has made great contributions to the development of modern display design. The purpose of this study is to use the combination of modern technology and traditional art to realize the cohesion of traditional environmental art and promote the economic and cultural development of the city and society. This experiment uses 3D virtual reality virtual technology, which usually takes the form of wearing glasses. There's a screen in front of your eyes. The sound can be transmitted via speakers or acoustics, so that people have an exciting feeling. The application of virtual reality technology to environmental art must follow three principles: the principle of truth in content, the principle of application in form and the principle of the quantity checked. Taking into account the virtual environment art projection function and the degree of user appreciation and referring to the virtual implementation method evaluation indicator in reality, five indices are also formed, such as degree of interaction, degree of photography, degree of function, degree of use, and degree of extension. The experimental results show that the weights of fast and accurate indexes are 0.74 and 0.36, respectively. Virtual interaction technology presents unlimited possibilities, breaks through the narrow nature of traditional display mode, opens up the current real exhibition development space, and provides new thinking for the design of environmental art. [ABSTRACT FROM AUTHOR]

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The three-dimensional intelligent simulation of image art design is an important means of current image art design, which is affected by many factors. The traditional 3D intelligent simulation technology has certain defects, which leads to certain defects in 3D artwork. This paper builds a three-dimensional art design system based on dynamic image detection and genetic algorithm. The system simulates the actual dehazing method, and this paper proposes a dehazing algorithm suitable for this system and proposes to use bilateral filtering instead of median filtering. Because bilateral filtering has good edge retention, it can eliminate the blockiness caused by median filtering. Moreover, this paper uses FMM (Fast Marching Method) algorithm to repair the image. In order to verify the performance of the model, this paper conducts quantitative evaluation through system simulation and user satisfaction survey methods. The research results show that the method proposed in this paper has a certain effect and can be applied to practice. [ABSTRACT FROM AUTHOR]

Traditional art design models are inefficient and difficult to control the modal characteristics of images. Based on the actual needs of artistic design, this paper builds an intelligent model of artistic design image modal analysis based on machine learning technology and image recognition technology, and proposes a feature extraction method based on wavelet transform and fuzzy logic and an art image classification method based on rotating quaternion wavelet transform. Moreover, this paper calculates the activation intensity value corresponding to each fuzzy area in the fuzzy feature space and normalizes these activation intensity values to form the artistic image feature vector. In addition, this paper uses rotating quaternary wavelet transform to decompose the art image, and then calculate the energy and standard deviation of each decomposed sub-band coefficient. Finally, this paper uses support vector machines to recognize artistic images. The experimental research shows that the model constructed in this paper has certain effects. [ABSTRACT FROM AUTHOR]

There are many coastal cities in China, with dense personnel and rapid economic development. Nuclear power plants, ports, and other major engineering facilities have been built, and their strategic position is very important. According to the corresponding gas situation of China's coastal cities, the overall goal of China's coastal cities is put forward: the construction of coping with climate change conforms to the climate situation of coastal cities in China. It has strong recovery ability after being affected by climate and can also adapt to long-term slow climate change, so that it will not collapse when encountering climate disasters. According to the above overall objectives, it is proposed that China's coastal cities should adhere to the principles of "planning guidance, land and sea planning, independent adaptation, active emission reduction, and increasing flexibility" to cope with climate change. The application of natural interactive design in the visual design of urban image is more and more. Therefore, in urban design, especially in coastal cities, based on the characteristics of climate and environment along the coastline of GIS system, the design concept adopts the method of returning to nature. From the most basic communication language and behavior mode between people, the characteristics of climate environment and the concept of new media era are integrated into the urban form like in design. [ABSTRACT FROM AUTHOR]

With the rapid development of artificial intelligence technology, the way we interact with products and the environment has undergone great changes compared with the past. While the technology of the artificial intelligence era affects our lives and redefines our relationship with machines, it is also changing our aesthetic and perception of art design. The article mainly starts from the perspective of art design interaction mode and experience innovation, and studies the multi-dimensional aesthetic perception and interaction mode of art design in the era of artificial intelligence in human vision, touch and hearing. [ABSTRACT FROM AUTHOR]

3D-printing (3DP) technology has become widespread over the past few years and has been applied in a number of areas, including the industrial design of tools and moulds, fashion design, and film and television production. Manufacturing products using 3DP has advantages: it accelerates the design process and lowers production time and costs. However, despite the fact that the use of 3DP in creating props and appliances for films and television is well-known, few papers have effectively studied this phenomenon. To this end, in this paper we describe our own experience to recreate ancient Chinese armour using 3DP for movies and discuss how our methods may be applied to the broader field. We use a Chinese army combat uniform, as an example, presenting in-detail the steps to designing, manufacturing, and processing this costume. We then analyse the advantages and disadvantages of 3DP and specific printers. As the use of 3DP in complex design is an emerging topic, we hope that this research will provide designers with information about the use, benefits, and challenges of 3DP in the design process. [ABSTRACT FROM AUTHOR]

Tian, Y. and Yang, L., 2020. Cultural and artistic design of coastal cities based on marine landscape. In: Gong, D.; Zhang, M., and Liu, R. (eds.), Advances in Coastal Research: Engineering, Industry, Economy, and Sustainable Development. Journal of Coastal Research, Special Issue No. 106, pp. 431–434. Coconut Creek (Florida), ISSN 0749-0208. The ocean has endowed open and shared spaces to coastal cities. The marine culture brought by marine landscapes affects the development and dissemination of culture and art in coastal cities and is an important source for the unique regional cultural landscapes of coastal cities. Based on the development of regional marine culture, this study aims to explore the role of marine landscapes in the cultural and artistic design of coastal cities and proposes corresponding strategies for cultural construction and development. The research results show that a beautiful marine landscape can be created in each coastal city; the basic elements of marine landscape design include conceptual elements, humanistic elements, natural elements, and artificial environment elements. The cultural and artistic design process in coastal cities must not only meet the requirements of urban development strategy, resource allocation, industrial layout, spatial pattern, and city image, but also adapt to the marine cultural atmosphere. This study provides a theoretical basis for accelerating the integration of marine culture into the cultural and artistic design of coastal cities. [ABSTRACT FROM AUTHOR]