Innovative Design Research Articles

Eastern Aesthetic Elements and Emotional Expression in Visual Communication

With the continuous advancement of globalization, the frequency of cross-cultural communication and interaction is increasing day by day. As a key way of information transmission, visual communication design not only plays a practical role as a messenger, but also has profound cultural connotations embedded in it. This paper aims to investigate and explain the application of Oriental aesthetic principles in the field of visual communication design and its effect on emotional externalization. By examining the fundamental definition and diachronic changes of the Oriental aesthetic concept, this paper intends to analyze the interpretation of these elements in the modern form of expression, in order to show how the iconic symbols such as ink painting, calligraphy art, and traditional symbolic totems are revitalized in the innovative design, and stimulate the emotional resonance in the viewer's heart.By analyzing a number of successful cases at home and abroad, this study not only demonstrates the unique charm of Oriental aesthetic elements in enhancing cultural identity, but also explores how to overcome the challenges brought by cultural differences and promote the integration and development of Eastern and Western cultures in a diversified design environment. Finally, this paper summarizes the potential trend of Oriental aesthetics in the field of visual communication design in the future, and puts forward corresponding practical suggestions.

High Entropy Ceramics for Electromagnetic Functional Materials

AbstractMicrowave absorbing materials play an increasingly important role in modern electronic warfare technology for enhancing electromagnetic compatibility and suppressing electromagnetic interference. High‐entropy ceramics (HECs) possess extraordinary physical and chemical properties, and more importantly, the high tunability of multi‐component HECs has brought new opportunities to microwave absorbing materials. Rich crystallographic distortions and multi‐component occupancies enable HECs to have highly efficient microwave absorption properties, excellent mechanical properties, and thermal stability. Therefore, the structural advantages of HECs are integrated from comprehensive perspectives, emphasizing on the role of dielectric and magnetic properties in the absorption phenomenon. Strategies are proposed to improve the microwave absorption capacity of HECs, including composition optimization, microstructure engineering, and post‐treatment technology. Finally, the problems and obstacles associated with high‐entropy materials (HEMs) research are discussed. The innovative design concepts of high‐entropy microwave absorbing ceramics are highlighted.

Electrochemical Methods for Nutrient Removal in Wastewater: A Review of Advanced Electrode Materials, Processes, and Applications

In response to the increasing global water demand and the pressing environmental challenges posed by climate change, the development of advanced wastewater treatment processes has become essential. This study introduces novel electrochemical technologies and examines the scalability of industrial-scale electrooxidation (EO) methods for wastewater treatment, focusing on simplifying processes and reducing operational costs. Focusing on the effective removal of key nutrients, specifically nitrogen and phosphorus, from wastewater, this review highlights recent advancements in electrode materials and innovative designs, such as high-performance metal oxides and carbon-based electrodes, that enhance efficiency and sustainability. Additionally, a comprehensive discussion covers a range of electrochemical methods, including electrocoagulation and electrooxidation, each evaluated for their effectiveness in nutrient removal. Unlike previous studies, this review not only examines nutrient removal efficiency, but also assesses the industrial applicability of these technologies through case studies, demonstrating their potential in municipal and industrial wastewater contexts. By advancing durable and cost-effective electrode materials, this study emphasizes the potential of electrochemical wastewater treatment technologies to address global water quality issues and promote environmental sustainability. Future research directions are identified with a focus on overcoming current limitations, such as high operational costs and electrode degradation, and positioning electrochemical treatment as a promising solution for sustainable water resource management on a larger scale.

The Great Controversy of Obstructive Sleep Apnea Treatment for Cardiovascular Risk Benefit: Advancing the Science Through Expert Consensus. An Official American Thoracic Society Workshop Report.

The prevalence of obstructive sleep apnea (OSA) is on the rise, driven by various factors including more sensitive diagnostic criteria, increased awareness, enhanced technology through at-home testing enabling easy and cost-effective diagnosis, and a growing incidence of comorbid conditions such as obesity. Treating symptomatic patients with OSA syndrome to enhance quality of life remains a cornerstone approach. However, there is a lack of consensus regarding treatment to improve cardiovascular disease (CVD) outcomes, particularly in light of overall negative results from several randomized controlled trials (RCT) indicating no benefit of positive airway pressure (PAP) therapy on primary and secondary CVD events. These RCTs were limited by suboptimal PAP adherence, use of composite CVD outcomes, and limited diversity and generalizability to Sleep Clinic patients. As such, this workshop assembled clinical experts, as well as researchers in basic and translational science, epidemiology, clinical trials, and population health to discuss the current state, and future research directions to guide personalized therapeutic strategies and future research directions in OSA. There was overall consensus among workshop participants that OSA represents a heterogeneous disease with variable endotypes and phenotypes, and heterogeneous responses to treatment. Future research should prioritize employing multi-modal therapeutic approaches within innovative and adaptive trial designs, focusing on specific subgroups of OSA patients hypothesized to benefit from a CVD perspective. Future work should also be inclusive of diverse populations and consider the life-course of OSA to better comprehend treatment strategies that can address the disproportionate impact of OSA on racially minoritized groups. Further, a more holistic approach to sleep must be adopted to include broader assessments of symptoms, sleep duration, and comorbid sleep and circadian disorders. Finally, it is imperative to establish a sleep research consortium dedicated to collecting raw data and biospecimens categorized by OSA subtypes. This will facilitate mechanistic determinations, foster collaborative research, and help bolster the pipeline of early-career researchers.

Case Study of Transforming and Scaling Entrepreneurial Internship Access in IHE

This case study explores innovative approaches to expand access to high-quality internships and improve equitable student outcomes. It focuses on Lehigh University’s virtual Innovation Internship program, partnered with the Nasdaq Entrepreneurial Center and Epixego Inc. The program aims to address challenges in traditional internships, such as hidden curriculum, false narratives, and unequal social environments. By incorporating self-assessment of learning competencies and enhancing student agency, the program doubled its capacity to 40 students. The study measured student self-efficacy, occupational identity choice, and outcome expectations based on various factors. Results showed that students changed internship preferences across occupation categories and experienced increases in entrepreneurial self-efficacy (3%), occupational identity (7%), and perception of entrepreneurship education (4%). This multifaceted approach demonstrates the potential for innovative internship designs to improve accessibility and student development outcomes.

Research on the Innovative Design of Tourism Cultural and Creative Products Based on Intangible Cultural Heritage

Under the background of the integration of culture and tourism, elements of intangible cultural heritage have been widely used in the design of tourism cultural and creative products, which makes tourism cultural and creative products more characteristic of regional culture. This not only broadens the cultural connotation and promotes the diversified development of tourism cultural and creative products, but also promotes the protection and inheritance of intangible cultural heritage. This paper analyzes the practical significance of the fusion of traditional and modern innovation in the design of tourism cultural and creative products from the aspects of innovative attributes and the design application of intangible cultural heritage.

Research on the Application of Smart Home in Interior Design

Abstract: With the rapid development of science and technology, the smart home in the field of interior design came to prominence. This paper discusses the application of smart home in interior design in the current environment. Smart home integration of advanced technology, covering intelligent lighting, home appliances, security, and environmental control systems. It provides designers with new creative ideas, challenges the traditional design mode, and promotes the perfect combination of technology, and art to meet people's pursuit of a high quality of life. For the residents, a smart home brings a new life experience, providing a comfortable, convenient, safe and personalized living environment. Therefore, this paper combines the new concepts, methods, and elements brought by smart home to interior design, analyses how smart home injects new vitality and innovative elements into interior design, and finds that the smart home opens up new dimensions, enriches the functional connotation, provides aesthetic inspiration, and changes the design process and method for interior design, that smart home is of great significance in promoting interior design innovation and change.

Quality Dimensions of Travel Products: A Research Perspective

This paper also explores the impacts and benefits of enhancing the quality of travel products using the four dimensions: conformity, durability, design innovation and improvement, and brand image.. It is found that high-quality travel products can not only improve tourists' satisfaction and promote word-of-mouth communication but also enhance brand image and market competitiveness, thus driving the development of related industries(Khan, M. S., et al. (2020). However, the improvement of travel product quality also faces many challenges, such as homogenized competition in the market, insufficient professionalism of service personnel, and lack of brand strategy. In response to these problems, this paper proposes future directions for research and practice, including strengthening product innovation and formulating a systematic brand-building strategy. By synthesizing the research on China's travel product quality, this paper aims to provide valuable references for academics and the industry and to provide theoretical support and practical guidance for improving travel product quality.

Research on innovative design of intelligent wearable products based on human machine engineering and bionics

Designing intelligent wearable products entails integrating human factors, engineering, and bionics to develop ergonomic, efficient and convenient products. Human-machine engineering is a discipline that addresses the integration between the user wearing a particular system and improving the relationship between the user and the system. At the same time, bionics is an approach that aims to mimic biological systems and structures to enhance the performance of a particular product. This research explores the possibility of integrating these specializations to design new and enhanced wearable technology products with improved usability, convenience, and flexibility for practical usage. A detailed analysis of human biomechanics and ergonomic requirements established design parameters to ensure that wearable devices could be seamlessly integrated into daily life without hindering user movement. Bionic principles, such as the flexibility of animal joints and the energy-efficient movements of natural organisms, were applied to optimize the mechanical and structural aspects of the devices. This approach enabled the creation of products that mimic the natural dynamics of the human body, offering improved responsiveness and functionality. Prototypes were developed based on human-centred design principles and evaluated using simulation and testing environments. Wearables such as exoskeletons, bright clothing, and health-monitoring devices were examined for their ability to adapt to various physical conditions and environmental changes. Results demonstrate a significant increase in user comfort, reduction in mechanical strain, and enhanced performance, validating the effectiveness of integrating human-machine engineering and bionics in wearable design.

Revolutionizing agri-food technology: Development and validation of the Portable Intelligent Oil Recognition System (PIORS)

The increasing demand for high-quality vegetable oils has amplified the need for efficient, and accurate, oil recognition systems. This paper introduces the Portable Intelligent Oil Recognition System (PIORS), a pioneering advancement in the field. PIORS stands as the first-ever portable, AI-powered device tailored for rapid and accurate oil type identification, capable of delivering results within a mere five seconds. Using advanced machine learning, PIORS can distinguish between various oil types such as sesame, black seed, flaxseed, and almond oils, ensuring the quality and safety of the final product. The device's innovative design integrates an advanced sensor array with seamless Bluetooth connectivity, offering real-time data synchronization with mobile applications. Several Machine learning models, including Support Vector Machines (SVM), AdaBoost, Random Forest, K-Nearest Neighbors (K-NN), Gradient-Boosting Decision Tree (GBDT), and Extreme Gradient Boosting (XGBoost) were implemented and thoroughly validated to obtain correct categorization. The results show that the XGBoost instantaneous classification algorithm continuously beat the competition, obtaining an astounding success rate of 97 percent in predicting and differentiating between the four oil classes. PIORS not only sets a new standard for speed and efficiency in oil quality assessment but also paves the way for groundbreaking applications in food safety, environmental monitoring, and quality control processes. This paper details the development, implementation, and validation of PIORS, showcasing its potential to revolutionize the agri-food industry with its cutting-edge, AI-driven approach to oil recognition.

Lightweight aircraft design: Integrating biomechanics and algorithm optimization for drone construction using paper materials

Lightweight aircraft design emphasizes materials like composites, alloys, and advanced polymers to reduce weight while ensuring structural integrity. Streamlined aerodynamics, efficient propulsion systems, and optimized component layout further enhance performance. The purpose of this research is to develop an innovative aircraft design model for drones, integrating algorithm optimization techniques and lightweight materials to enhance the performance and efficiency of drones with the utilization of open-source software. We apply this structure to the construction of drones with fixed-wing (FW) and vertical take-off and landing (VTOL) configurations. The aircraft’s body is constructed using lightweight materials such as glass fiber fabric (Gff) and extruded polystyrene foam (XPS), employing a vacuum-assisted wet layup technique for fabrication. Multi-objective Co-evolving Ant Colony Optimization (MC-ACO) was used to improve the construction of drones with VTOL and FW capabilities. This strategy enabled it to be easier to achieve the trade-offs required for a generalist drone design, such as range, payload capabilities, and swarm operations, which were then evaluated against commercially available software to evaluate the effectiveness. Incorporating biomechanics into the design method permits higher consideration of user interaction with drones. The findings indicate that low-fidelity architecture is a suitable starting point for prototyping under limited time frames. The paper concludes with a discussion of the technical constraints of employing free software, as well as some practical concerns for flight testing drones with hybrid configurations.

Comprehensive and Robust Anti-Jamming Dual-Electrode Pair Sensor.

Capacitive flexible sensors often encounter instability caused by temperature fluctuations, electromagnetic interference, stray capacitance effects, and signal noise induced by ubiquitous vibrations. The challenge lies in achieving comprehensive anti-jamming abilities while preserving a simplistic structure and manufacturing process. To tackle this dilemma, a straightforward and effective design is utilized to achieve comprehensive and robust anti-jamming properties in capacitive sensors. Electrospinning thermoplastic polyurethane (TPU) fiber mats soak with ionic liquid (IL) to create a co-continuous structure (TPU@IL) with high ionic conductivity and dielectric constant, which acts as the sensing units. The sensing mechanism of the TPU@IL with multiple electrode pairs encapsulated by polyethylene terephthalate (PET) is systematically elucidated. The optimal dual-electrode pair design for capacitive and resistive sensors, which have different sensitivities to temperature and stress, simultaneous realizes temperature-stress dual-mode sensing. Remarkably, the sensitivity curve of the TPU@IL/PET capacitive sensor exhibits an intriguing rarely reported S-shape with an adjustable step stress point. No liquid leakage even during extensive stress-strain cycling (>4000 cycles). Despite a slight compromise in sensitivity and response time, the TPU@IL/PET sensor demonstrates exceptional electromechanical stability, reliability, and powerful anti-jamming abilities against various interferences. A simple yet innovative sensor design enhances the performance and applicability of capacitive sensors in challenging environments.

Implementing an adaptive reuse on industrial buildings: a proposal for transforming Erbil’s Silo in Kurdistan-Iraq into a hotel

Industrial buildings, serving as markers of cultural heritage, connect our cultural identity from the past through the present and into the future. Unfortunately, many of these buildings lose their identity when they are converted into another function. Through the case study analysis (the Silo of Erbil City), a qualitative method is employed to examine design strategies and spatial transformations in recent adaptive reuse projects of existing structures. Through the literature review, this research investigates the importance of adaptive reuse and heritage buildings, underscoring their historical and theoretical underpinnings, and subsequently examines contemporary approaches to architectural criteria towards habitation for existing structures in the public, creative, and cultural domains. The study findings identify common fundamental elements of industrial heritage adaptive reuse and innovative design strategies applied in recent adaptive reuse projects, highlighting the potential to transform neglected or vacant abandoned buildings into urban open spaces. The study uses a comprehensive methodology involving case study analyses and diverse data collection techniques. The case study properties are the structural systems, natural lighting, and the surrounding open spaces. As a result, a hotel with a multipurpose hall, and a museum dedicated to the history of the Silo have been proposed, aiming at conserving the valuable heritage in this industrial area as well as providing an alternative perspective for the adaptive reuse of industrial structures in Erbil city. Finally, the implications of the research for the economic and social dimensions of urban development lie in understanding and promoting sustainable preservation strategies. This work is considered the first step for future research in Iraq, specifically in Kurdistan Region. The research concludes that the Silo of Erbil is one of the successful examples of the process of reusing buildings. It also concludes that less intervention in reusing a building can protect the building identity.

PKM Rekayasa Pembuatan Kartu Undangan Digital Sebagai Media Usaha Mandiri

The rapid advancement of information technology has significantly impacted various sectors, including theinvitation printing industry. With the increasing use of the internet in Indonesia, digital invitation businesseshave become an attractive opportunity, offering practicality and cost efficiency compared to traditional printedinvitations. This writing aims to explore the development of digital invitation cards as an independent business,focusing on appealing designs and effective marketing strategies through online platforms and social media.Through literature study methods and the implementation of community service programs, it was found thatdigital invitations have several advantages. These advantages include lower costs, easy access, and customizableinteractive features such as animations, videos, and direct links to important event information. The importanceof implementing communicative and interactive designs is key to attracting consumer attention. An attractivedesign not only serves as a visual appeal but also conveys information more clearly and effectively.Additionally, using social media as a marketing channel can enhance market reach, allowing for rapiddissemination of digital invitations to a wider audience. With the right approach, digital invitation businessescan meet the market's growing demand for digital solutions. Innovation in design and marketing will create newbusiness opportunities for individuals or groups looking to leverage information technology, making thisindustry increasingly relevant in today's digital era. Community involvement in this process can also strengthenlocal communities and enhance digital literacy among users.

Penerapan Metode Stable Diffusion Dengan Fine Tuning Untuk Pola Endek Bali

Endek Bali fabric is a cultural heritage of Bali renowned for its traditional decorative motifs, including floral, fauna, patra, and diamond patterns. Although rich in cultural value, artisans often face challenges in creating new designs that align with market trends while preserving cultural authenticity. Artificial Intelligence (AI) technology, particularly text-to-image generation models, offers a solution to this issue by streamlining the design process and enabling the exploration of new motifs. The Stable Diffusion model, introduced by Stability.AI in 2022 and open source, can be utilized to generate Endek Bali patterns through Fine Tuning techniques. Fine Tuning allows the model to be adapted to specific domains, enhancing its performance in generating textile patterns based on textual descriptions. This study aims to apply the Stable Diffusion model and Fine Tuning techniques to create new patterns and motifs. By using this model, it is hoped that innovative designs can be produced while maintaining the authenticity and local cultural values of Bali. The research demonstrates that the Fine-Tuned Stable Diffusion model is effective in creating Endek Bali patterns with high accuracy, as evaluated by Clip Similarity, with the highest scores achieved for Floral Patterns (92.43), followed by Decorative (free-form motifs) Floral (88.77), Decorative (free-form motifs) Geometric (87.94), and Decorative (free-form motifs) (85.79). These findings indicate the model’s flexibility and effectiveness in producing intricate textile designs, enabling designers and artisans to generate complex and innovative patterns solely from textual descriptions while preserving Bali’s cultural values.

Innovative design and sensing performance of a novel large-strain sensor for prestressed FRP plates

Owing to the low measuring range of traditional fiber Bragg grating (FBG) sensors and the complexity, imprecision, and lack of practicality in existing large-strain sensors, this paper introduces a novel type of large-strain sensor based on pre-relaxation and continuous sensing technology. This design aims to realize the whole-process strain monitoring of prestressed fiber reinforced polymer (FRP) plates. Static tensile tests were conducted on 9 large-strain sensor specimens. The effects of pre-relaxation degree, section number, pre-tension time, and prestressing level were evaluated. The results reveal that, the pre-relaxed sensor, proved its efficacy in capturing the strain pertinent to the post-tensioned operational state of the FRP plate, and a sensing performance of up to 18,923 με can be facilitated and further extended by a pre-relaxation and continuous sensing technique. Moreover, it is recommended that during the fabrication of the large-strain sensor, two pre-tensions be applied, with a prestressing level between 115% and 125% of the pre-relaxation degree.

Research on the A* Algorithm for Automatic Guided Vehicles in Large-Scale Maps

The traditional A* algorithm faces the challenges of low search efficiency and large node extension range in the field of path planning. These directly restrict the overall performance of the algorithm. In this study, we aimed to improve the search efficiency and path planning quality of the A* algorithm in complex and large-scale environments through a series of optimisation measures, including the innovation of weight design, flexible adjustment of the search neighbourhood, improvement of the heuristic function, and optimisation of the node selection strategy. Specifically, this study innovatively introduces the local obstacle rate as the core index of weight design, and it dynamically adjusts the weights according to the change of the obstacle rate during the node movement process, which effectively reduces the search space and significantly improves the search speed. At the same time, according to the real-time change of the local obstacle rate, this study dynamically adjusts the range of the search neighbourhood, so that the algorithm can choose the optimal search strategy according to different environmental information. In terms of the improvement of the heuristic function, this study adopted the diagonal distance as the benchmark for cost estimation, and it innovatively introduces the angle coefficient to reflect the complexity of path turning, thus providing the algorithm with a more accurate guidance for the search direction. In addition, this study optimises the node selection method by drawing on the idea of simulated annealing, which eliminates the need to calculate and compare all possible surrogate values during the node selection process, thus significantly reducing the running time of the algorithm. The results of the simulation experiments fully verify the effectiveness and practicality of the improved algorithm. Compared with the traditional A* algorithm, the improved algorithm achieved significant optimisation in terms of the average running time, the number of expansion nodes, and the path length, with the average running time shortened by 84%, the number of expansion nodes reduced by 94%, and the path length also shortened by 2.3%.

Bouncing back from emotional ups and downs: insights in emotional recovery using survival analyses of burst ESM data.

Many experience sampling (ESM) studies suggested that high resilience is reflected by quickly recovering one's emotional baseline. However, former studies relied on coarse data and did not look into differential recovery from emotional ups and downs. This preregistered proof-of-concept study therefore used high-resolution data collected in 2022 to compute emotional recovery after high levels of positive versus negative emotions. Adults (N = 68) participated in a three-week ESM study with eight assessments per day, complemented by short-spaced burst assessments. Resilience was assessed at baseline (trait-level; TR) and daily (day-level; DR). Multilevel survival analyses showed that high DR predicted faster returns from negative emotions, but also delayed returns following positive emotions (exp(β) = 1.32, p = 0.006). Instead, TR did not relate to emotional recovery (exp(β) = 0.85, p = 0.067). These findings were generally robust across different sensitivity analyses. This illustrates how innovative ESM designs combined with time-to-event analyses may further our insight in emotional recovery and the timescale at which it unfolds.

Visualisation Design Ideation with AI: A New Framework, Vocabulary, and Tool

This paper introduces an innovative framework for visualisation design ideation, which includes a collection of terms for creative visualisation design, the five-step process, and an implementation called VisAlchemy. Throughout the visualisation ideation process, individuals engage in exploring various concepts, brainstorming, sketching ideas, prototyping, and experimenting with different methods to visually represent data or information. Sometimes, designers feel incapable of sketching, and the ideation process can be quite lengthy. In such cases, generative AI can provide assistance. However, even with AI, it can be difficult to know which vocabulary to use and how to strategically approach the design process. Our strategy prompts imaginative and structured narratives for generative AI use, facilitating the generation and refinement of visualisation design ideas. We aim to inspire fresh and innovative ideas, encouraging creativity and exploring unconventional concepts. VisAlchemy is a five-step framework: a methodical approach to defining, exploring, and refining prompts to enhance the generative AI process. The framework blends design elements and aesthetics with context and application. In addition, we present a vocabulary set of 300 words, underpinned from a corpus of visualisation design and art papers, along with a demonstration tool called VisAlchemy. The interactive interface of the VisAlchemy tool allows users to adhere to the framework and generate innovative visualisation design concepts. It is built using the SDXL Turbo language model. Finally, we demonstrate its use through case studies and examples and show the transformative power of the framework to create inspired and exciting design ideas through refinement, re-ordering, weighting of words and word rephrasing.

Path Algebra-Driven Classification Solution to Realize User-Centric Performance-Oriented Virtual Network Embeddings

The intense diversity of the Next-Generation Networking environments like 6G and the forthcoming deployment of immersive applications with varied user-specific requirements transform the efficient allocation of resources into a real challenge. Traditional solutions like the shortest path algorithm and mono-constraint methodologies are inadequate to handle customized user-defined performance parameters and effectively classify physical resources according to these intricate demands. This research offers a new evaluation mechanism to successfully replace the aforementioned traditional path ranking and path selection techniques. Specifically, the proposed framework is integrated with optimization-oriented metrics, each indicating a unique aspect of performance for evaluating candidate network paths. The deployed metrics are then algebraically synthesized to provide a distinctive multidimensional description of the examined substrate resources. These primary and composite metrics adhere to the fundamental monotonicity and isotonicity properties of a Path Algebra; hence, the validity and optimality of the proposed evaluation mechanism is guaranteed by design. To tackle the complexity created by the variety of human-centric customization, a novel methodology that analyzes and determines the weighted influence of the synthesized metrics depending on the characteristics of the served user-centric application is also introduced. The chosen suitable weights address performance-oriented mission-critical tailored objectives for adaptive optimizations. Its innovative algebraic design allows it to successfully describe and rank candidate paths in a versatile way, whether in legacy or modern architectures. The experimental data of the first scenario show that 62.5% and 50% of highlighted path evaluations proposed by the shortest path and unidimensional constraint strategies, respectively, suffer from moderate performance-oriented values compared to the proposed framework. Likewise, the results of the second examined scenario reveal that the proposed composite metric yields more suitable path rankings by 50% in contrast to its traditional counterparts, rendering the contested evaluation mechanisms obsolete.