International Journal of Arts and Technology (18 papers in press)

Regular Issues

• Cosmetic Packaging Design Method Integrating Shape Grammar from the Perspective of Artificial Intelligence Generated Content: a Case Study of Song Porcelain Patterns  
  by Zhenyu Li, Zhan Gao 
  Abstract: Abstract: This paper, taking the patterns of Song Dynasty porcelain as an example, explores novel approaches to cosmetic packaging design. First, a database of Song Dynasty porcelain patterns is set up. Then, through applying the derivation method based on shape grammar, innovation is carried out, during which the forms of these patterns are deconstructed and reconstructed while the cultural symbols are retained. Next, a low-rank adaptation model is trained with the Stable Diffusion model. By combining relevant functions along with the conditional control function of ControlNet, cosmetic packaging design schemes in the style of Song Dynasty porcelain are generated. Finally, the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) is used to rank and optimise these design schemes. This comprehensive approach boosts the design's creativity, diversity, scientific nature, and rationality, offering fresh ideas for cosmetic packaging design.
  Keywords: Keywords: Artificial Intelligence; Stable Diffusion; Shape Grammar; Low-Rank Adaptation model; Cosmetic Package design;.
  DOI: 10.1504/IJART.2025.10072005
   
  
• Emotional Experience in Ethnic Vocal Music Appreciation Reflects AI Interactive Technology  
  by Yan Chen 
  Abstract: This research mainly discusses the important manifestation of the emotional experience in the music appreciation of ethnic vocal music in the AI interactive technology.The system adopts a three-layer BP neural network design, the input is the feature vector of the MIDI ethnic instrument music segment, and the output vector represents the music emotion. The music feature extraction module mainly completes the reading and analysis of music fragments in MIDI format, extracts the basic features of music and abstract features such as rhythm, melody, mode, tune, and harmony, and stores the feature information in a dynamic database. In the process of music feature extraction and recognition, the system first reads the note queue and speed information queue of ethnic vocal music in MIDI format, and then analyzes and calculates the basic characteristics of music, music mode and melody characteristics, and music rhythm characteristics.
  Keywords: AI Interaction; Emotional Experience; Music Appreciation; BP Neural Network; Music Features.
  DOI: 10.1504/IJART.2025.10072119
   
  
• Opera Audio Understanding and Synthesis via Neural Network Models: from Recognition to Generation  
  by Jie Pan 
  Abstract: This study proposes a composite model for opera audio recognition and style generation. The model integrates chaotic fingerprint coding, deep neural networks, and generative networks for style transfer. The model uses a 20-bit chaotic audio fingerprint based on logistic mapping and time-frequency peaks. This technology can achieve efficient compression and robust recognition. The accuracy of method in a noisy environment is 92.3%, which is 12.5% higher than that of traditional methods. The DNN-LightGBM cascade structure effectively models features and efficiently classifies features in 19 opera categories with an accuracy of 8895%. In terms of style transfer, generative adversarial network with orthogonal style loss function separates timbre and style and reduce Mel cepstral distortion by 18.3%, from 5.24 to 4.87. In addition, spectrum-based unsupervised linear style encoder improves the robustness of the transfer by 23.6% under various accompaniment conditions. The framework has high recognition accuracy, high-quality style transfer, and strong adaptability.
  Keywords: Opera Audio; Neural Network Models; Audio Recognition; Audio Synthesis; Generative Modeling.
  DOI: 10.1504/IJART.2026.10072740
   
  
• Assessment of Deep Learning algorithms for Damage Segmentation in Indian Murals  
  by Anshul Kumar Yadav, Ronit Kunkolienker, Dhiraj Sangwan 
  Abstract: Murals on walls of the havelis in Rajasthan have become damaged, and Image Inpainting has emerged as a potent solution to the problem. Masking damage is a crucial step for inpainting algorithms to avoid learning from damaged regions. Therefore, this study focuses on damage identification, utilising prominent architectures, including U-Net and its derivatives, as well as adversarial networks. The study also explores the effect of dense conditional random field (dCRF) and major voting ensemble algorithm. The results show that using dCRF modelling and an ensemble approach improves the average structural similarity index measure (SSIM) score from 0.9672 to 0.9703 for the test dataset. Alone, dCRF improves the output of the worst-performing model, Pix2Pix (modified), by 5.02 %. The suggested method also outperforms the generic adversarial image translation networks for mural damage segmentation on the test dataset by up to 5.45% in the mIoU and 3.61% in the mean DSC score.
  Keywords: Damage annotation; Mural restoration; Convolutional neural networks; Generative adversarial networks; Ensemble learning.
  DOI: 10.1504/IJART.2025.10072772
   
  
• Quantitative Assessment of Rural Handicraft Industrialisation Pathways: Multiple Regression Analysis of Art Design Curriculum's Impact on Community Cultural Capital Accumulation  
  by Zhe Liang 
  Abstract: This study explores how art design curriculum interventions impact rural handicraft economies through cultural capital accumulation. Analysing data from 412 respondents across 27 rural communities, it measures four cultural capital dimensions: skills, products, institutional recognition, and knowledge networks. Results show curriculum significantly enhances cultural capital directly (?=0.28, p<0.05) and indirectly via knowledge transfer (?=0.37, p<0.01), with a strong total effect (?=0.65, p<0.001). Institutional recognition correlates with market expansion (r=0.82, p<0.01), while knowledge networks link to production sustainability (r=0.76, p<0.01). The model explains 86% of economic performance variance, with regional variations (Southern: R2 = 0.85; remote: R2 = 0.64). Innovative industrialisation yields higher ROI (cultural: 68%; digital: 60%) than traditional methods. The findings support targeted investments and highlight contextual influences on cultural capital conversion.
  Keywords: Cultural capital quantification; Multiple regression modelling; Rural handicraft industrialisation; Art design education; Sustainable rural development.
  DOI: 10.1504/IJART.2026.10073087
   
  
• Dynamic Technology in Dance Art: The Combination of Computer Simulation and Five-Position Footwork Movements  
  by Sitong Chen, Jian Yang 
  Abstract: Traditional ballet dance teaching is teacher-centred. Due to differences in regional development, this teacher-centred approach has the problem of unbalanced teaching resources and a lack of high-quality resources. This paper proposes a dance movement teaching system using computer simulation technology to solve this dilemma. Taking the teaching of the five-position footwork of the basic ballet movement as an example, the teaching system processes the students movements in real-time through the mobile phone camera, extracts the key point sequence of the human skeleton based on the OpenPose algorithm, and evaluates the movement similarity with the optimised dynamic time warping (DTW) algorithm. Finally, the movements are annotated on the mobile phone screen and guided and corrected with voice broadcast. Compared with traditional one-on-one and one-to-many dance movement teaching by teachers, the action achievement rate (AAR) of students taught by this system reached 96.2% in the same period. In the hip external rotation angle test, the average angle difference decreased by 40.00% and 62.05%, respectively, and the standard deviation decreased by 55.74% and 64.34%, respectively. This fully demonstrates the advantages of this system in dance movement teaching and provides a new direction for the innovation of dance movement teaching.
  Keywords: Computer Simulation; DTW Optimisation; Ballet Five-Position Foot; Movement Compliance Rate; Hip External Rotation Angle.
  DOI: 10.1504/IJART.2026.10073427
   
  
• Personalized Art Font Design Based on Improved Generative Adversarial Networks  
  by Lele Yin, Qi Wang 
  Abstract: By adding residual connections, each layer in the generator depends on the previous layer's output, directly transmitting information through shortcut paths, and maintaining the stability of the network in deep training. Combined with style transfer technology, the artistic style is integrated with the font structure to further enhance the personalized characteristics of the generated font. Experiments show that the method in this paper significantly improves the quality, detail expression, and personalised style of the generated fonts. The structural similarity index (SSIM) of the generated font image and the target image pixel block is between 0.82 and 0.93, and the recognition accuracy of the generated font in the optical character recognition (OCR) model is not less than 0.7. The details of the generated font are very close to the target image, effectively making up for traditional generative adversarial networks' shortcomings in art font design.
  Keywords: Generative Adversarial Network; Residual Connection; Deep Convolutional Network; Style Transfer; Personalized Font Design.
  DOI: 10.1504/IJART.2026.10073612
   
  
• Creative Graphic Symbol Design based on Text Intelligent Generation Technology  
  by Jing Zhuo 
  Abstract: To convey information intuitively and accurately and innovate graphic symbol design, the definition and classification of graphic symbols are deeply studied in this paper. Based on its development status, this paper combined text intelligent generation technology to explore effectively. To show its design effect, this paper conducted experiments through data sets. The training similarity and visual communication were analysed respectively and compared with the design effect of traditional algorithms. The experimental results showed that under different topic classifications, the average topic relevance of creative graphic symbols designed based on text intelligent generation technology reached 90.67%. From the experimental results, it could be seen that the design of creative graphic symbols based on text intelligent generation technology was ideal, which was more consistent with the theme and more conducive to the transmission and expression of cultural connotation.
  Keywords: Creative Graphic Symbol Design; text generation Technology; Convolutional Neural Network; Visual Communication.
  DOI: 10.1504/IJART.2025.10073746
   
  
• Audiences' Acceptance towards Technological Integration: a Case Study using PCA and HCA Method to Analyse Experience on Augmented Reality Public Sculpture Exhibited at Kota Samarahan, Sarawak  
  by Valerie Michael, Muhammad Fauzan Abu Bakar 
  Abstract: The study aims to explore and reveal the possible potential of augmented reality in redefining audience interaction and artistic communication, specifically concerning the incorporation of Augmented Reality into the development of public sculpture. This research utilises quantitative approaches, specifically Principal Component Analysis (PCA), p-values, confidence intervals and Hierarchical Cluster Analysis (HCA), to identify the primary component influencing audience experiences. A total of 38 participants are eligible to participate in the study and the results indicated that augmented reality may improve interactive encounters, emotional engagement, and consequently, a deeper comprehension of the artist's representations. The article explain how augmented reality can connect traditional and digital art, foster inclusivity, and promote critical thinking among its audience. This placing of the findings within the art context highlights some cultural and pedagogical implications of AR technology in the emerging paradigmatic application of participatory art activities.
  Keywords: Augmented Reality; Audience Engagement; Innovative Arts; Participatory Arts; Artistic Community.
  DOI: 10.1504/IJART.2026.10074055
   
  
• Analysis of the Cultivation of Image Feeling Ability in Computer-Aided Painting Art Appreciation and Aesthetic Education  
  by Jiming Suo, Duorong Qiu 
  Abstract: Aesthetic education is a method of instructing students about art through inquiry, writing, and art-making activities. Students in art classrooms around the country are learning about virtual reality to stay up with the ever-changing demands of art and aesthetics in today's world. Computer-Aided systems for art design can improve efficiency, ease of use, storage and display convenience, and significantly increase objectivity. The Virtual Reality-based Aesthetic Art Education Teaching (VR-AAET) approach in the students' appraisal of painting skills will be examined. The interaction between action education and aesthetic education is explored in the suggested technique to analyse the vital function of Aesthetic Education (AE) in action teaching. Students' capacity to sense and comprehend the feeling can be developed by different aesthetic education methods, such as instructors' aesthetic education abilities, enhancing educational processes, and beautifying the teaching environment. The network model's appreciation ability differs from a typical painting course's, and performance is crucial. Overall, students' knowledgeability is 4.0, far better than the even value of 5.0, showing that the virtual reality platform has substantially boosted their art appreciation. As a result, a virtual platform model has been developed that significantly enhances students capacity to appreciate new concepts.
  Keywords: Virtual Reality; aesthetic education; art teaching; painting.
  DOI: 10.1504/IJART.2026.10074101
   
  
• Application of Digital Image Media Technology in Film Animation  
  by Yan Liu, Feng Tang 
  Abstract: The development of media technology in the digital age has enabled many traditional artists to achieve new developments in their creations. The emergence of this expression method has greatly enriched the forms of artistic expression. This paper studies the application of digital image media technology in film and television animation. In the experimental part, it is applied to teaching, and experiments are conducted on several processes of animation production. The experimental results show that its application effect in the post-production link is most obvious. The scores of the experimental class are mainly concentrated in the 80100 points stage. There are 20 students in Class A who have reached 90100 points, 18 students in Class B who have reached 90100 points, and only five students in Class C who have reached 90100 points, and only six students in Class D who have reached 90100 points. It can be seen that the application of digital image media technology has effectively improved the production effect of animation. At the end of the paper, a brief summary of specific technologies and applications is given.
  Keywords: Film and Television Animation; Digital Image Technology; Post Production; Image Fusion Algorithm.
  DOI: 10.1504/IJART.2026.10074102
   
  
• Construction of a 3D Art Visualization Platform Based on Digital Engineering and VR Technology  
  by Danyang Li, Zixin Wang 
  Abstract: To address issues such as irregular 3D sculpting modelling, distortion in rendering of ink paintings and oil paintings, and low efficiency in collaborative workflows for multi-source art assets, this paper utilises an enhanced NVIDIA Omniverse architecture to optimise data processing efficiency and VR device compatibility in 3D art visualisation. First, this paper implements point cloud data compression and mesh simplification using an improved KD-tree algorithm; secondly, it develops a PBR material converter to automatically map traditional materials to physically-based rendering materials. Furthermore, the system implements a USDZ scene description file generation process, supporting real-time asset updates, BIM-compatible path tracing rendering, and distributed ray tracing with OptiX acceleration. Finally, this paper validates the performance of the platform through experiments. The experimental results show that the improved platform reduces GPU memory usage by 35%, reduces rendering latency by 56%, and achieves a VR device compatibility rate of 98.6%.
  Keywords: Digital Engineering; Virtual Reality Technology; 3D Visualization; Data Processing; Cross-platform Adaptation.
  DOI: 10.1504/IJART.2026.10074163
   
  
• Multimedia Art Data Optimisation by Integrating UO-CRUSH and Q-learning Algorithm VR Technology  
  by Hongying Song, Xiaohong Wang 
  Abstract: A resource management framework based on virtual reality (VR) technology is proposed to address the limitations and poor presentation effects of traditional multimedia art data flat creation. It integrates the UO-CRUSH algorithm driven by resource interest and the Q-learning algorithm driven by user interest to optimise the storage and scheduling of multimedia art data. The experimental results show that the proposed model has an average computation time of 426 seconds, completes an average of 752 tasks in the maximum cycle, and has a uniform distribution of resource placement groups (137153). In the instance verification, the classification accuracy is not less than 90%, the interactive response speed is 172 ms, and the frame rate of the picture reaches 78fps, which combines good immersion and economy. This model effectively improves the optimisation effect of multimedia art data.
  Keywords: Multimedia art data; Virtual reality; Scalable replica hashing algorithm; Reinforcement learning algorithm; Resource management.
  DOI: 10.1504/IJART.2026.10074165
   
  
• Developing a Community Participation Strategy for the Preservation of Historic Buildings in Shanghai  
  by Lu Chen 
  Abstract: This study introduces a novel approach that is specifically designed to align with China's unique national circumstances, allowing for the active involvement of the community. We propose a "community participation framework" that incorporates distinctive local features, formulated through an extensive review and synthesis of both domestic and international literature, as well as drawing insights from effective community governance practices in China. The framework seeks to harmonise the interactions between community members, historic structures, and municipal authorities. Within this structure, these stakeholders can create a cohesive and self-sustaining system, mutually benefiting from the preservation efforts of historical architecture. To guarantee ongoing advancements in this initiative, oversight and management practices were implemented, utilising performance evaluation metrics to measure the protective measures' effectiveness. Our findings offer valuable insights for furthering the engagement of social forces in the conservation of historical buildings in China.
  Keywords: Community Engagement; Conservation of Historic Buildings; Layered Analysis; Framework Development.
  DOI: 10.1504/IJART.2026.10074166
   
  
• Quantitative Evaluation of the Effectiveness of Preservation of Modern Urban Residential Buildings in Shanghai (1910-1949)  
  by Lu Chen 
  Abstract: This study examines modern residential buildings in Shanghai 19101949), analysing the dynamic relationships among architecture, inhabitants, the environment, and society. Addressing the urgent need to conserve Shanghai historical structures, it establishes key evaluation metrics for preservation effectiveness. Employing a quantitative approach validated by a BP neural network model, the analysis demonstrates that current conservation strategies fail to fully harness their potential to drive economic growth, enhance resident quality of life, foster environmental sustainability, or enrich urban cultural heritage. Recognising the intrinsic link between historical preservation and collective well-being encompassing human, environmental, and societal dimensions the research develops optimisation strategies to maximise conservation outcomes. The goal is to significantly elevate the impact of preservation efforts on these buildings, establishing a benchmark for scholarly research, policy formulation, and heritage management in Shanghai and analogous contexts.
  Keywords: Quantitative Assessment of Conservation Effectiveness; AHP; FCE;BP.
  DOI: 10.1504/IJART.2026.10074167
   
  
• Building Immersive Virtual Reality Visualisation Display System based on Multi-Level Interaction for Metaverse  
  by Yong Zhang, Xiaocheng Zhou, Mengzi Zhang, Lei Ding, RongWang Yin 
  Abstract: Currently, art and design education primarily relies on two-dimensional image presentations, lacking support from immersive and interactive metaverse environments. This limits the ability to effectively demonstrate the dynamic aspects of the design process, thus hindering students in-depth understanding of the design process. This research uses the Unity engine as its platform, leveraging its material and lighting capabilities, to develop an immersive virtual reality (VR) visualisation system to enhance art and design teaching effectiveness. After testing, the results showed that the immersive VR visualisation system based on Unity engine technology achieved an average immersion score of 8.7, and the average task completion time was 2.76 seconds. Research shows that the system designed in this paper not only enhances the immersion and interactivity of teaching, enriches teaching content, and optimises the remote learning experience, but also provides strong support for innovation in educational technology.
  Keywords: Immersive Virtual Reality; Art Design; Visual Display System; Multi-level Interaction; Metaverse Background.
  DOI: 10.1504/IJART.2026.10074168
   
  
• Digital Preservation of Art and Architectural Motifs: a Technology-Integrated Design Framework for the Dimasa Heritage Monuments  
  by Swarnadeep Nath, Sourish Sarkar, Bhaskar Saha 
  Abstract: Cultural heritage, rooted in historical, cultural, and religious traditions, is essential to regional identity and national legacy. In Assam, Northeast India, diverse indigenous communities have shaped a rich architectural tradition. However, limited written records obscure much of this history, making material culture monuments, archaeological sites, and architectural remains a crucial source for reconstructing the regions understudied past. Among these contributions, the Dimasa emerged as prominent rulers who significantly shaped the architectural heritage of the region. Over time, though, the remnants from the kingdom have faced significant erosion due to various organic and environmental factors, risking the loss of invaluable relics without precise preservation and restoration. This study aims to digitally restore the structural integrity and design aesthetics of the Dimasa Kingdoms heritage monuments at Khaspur. Integrating 2D and 3D framework with terrestrial and aerial photogrammetry ensures accurate structural documentation, while close-range photography captures intricate design motifs. The combined datasets support a comprehensive design process aligned with the studys objectives. This imperative study holds the potential to ensure the digital preservation of the regions heritage monuments. Moreover, this effort may recreate novel opportunities as a resource for researchers and archaeologists, especially within the context of upcoming restoration and conservation efforts.
  Keywords: Dimasa kingdom; Architectural motifs; Art and technology; Digital restoration; Cultural heritage.
  DOI: 10.1504/IJART.2026.10074182
   
  
• Optimisation Strategy for Ceramic Cultural and Creative Product Design Combining Analytic Hierarchy Process and AlexNet  
  by Cong Wang, Qian Dong, Liangliang Lin 
  Abstract: To provide design optimisation strategies for ceramic cultural and creative designers, this article used AlexNet deep convolutional neural network to extract features from six popular ceramic cultural and creative products (Dehua white porcelain, Tangshan bone porcelain, Longquan celadon, Yixing purple sand, ceramic underglaze colour, and modern ceramic art). The feature vectors of each image were output, and the feature vectors were reduced to low dimensional feature vectors corresponding to colour, texture, shape, and pattern respectively. Based on the features extracted by AlexNet, experts gave preliminary ratings to the six major ceramic cultural and creative products. The hierarchical structure of the comprehensive evaluation of ceramic cultural and creative products was constructed, and the Analytic Hierarchy Process was applied to calculate the weights of the four indicators of color, texture, shape, and pattern of ceramic cultural and creative works.
  Keywords: Ceramic Design; AlexNet Algorithm; Analytic Hierarchy Process; Confusion Matrix; Feature Extraction.