Design Patterns Research Articles

Architecting a digital twin for wind turbine rotor blade aerodynamic monitoring

Digital twins play an ever-increasing role in maximising the value of measurement and synthetic data by providing real-time monitoring of physical systems, integrating predictive models and creating actionable insights. This paper presents the development and implementation of the Aerosense digital twin for aerodynamic monitoring of wind turbine rotor blades. Employing low-cost, easy-to-install microelectromechanical (MEMS) sensors, the Aerosense system collects aerodynamic and acoustic data from rotor blades. This data is analysed through a cloud-based system that enables real-time analytics and predictive modelling. Our methodological approach frames digital twin development as a systems engineering problem and utilises design patterns, design thinking, and a co-design framework from applied category theory to aid in the development process. The paper details the architecture, deployment, and validation of a ‘Digital Shadow’-type twin with simulation/prediction functionalities. The solution pattern is discussed in terms of its implementation challenges and broader applicability. By providing a practical solution to integrating all the digital twin components into a holistic system, we aim to help wind energy specialists learn how to transform a conceptual idea of a digital twin into a functional implementation for any application.

Façade Design Pattern Optimization Workflow Through Visual Spatial Frequency Analysis and Structural Safety Assessment

As the demand for highly efficient yet aesthetically pleasing, complex building envelope structures is rising worldwide, computational analysis and generative design tools are becoming ever so relevant. Previous methods for achieving a natural distribution of structural or shading elements in non-uniform façades are mostly based either on computer-generated pseudo-randomness or a literal biomorphic approach where a naturally occurring pattern is directly projected on the façade surface. As an alternative, this research introduces a novel technique for optimisation that utilises a two-dimensional Power Spectrum Analysis, suitable for numerically assessing the alignment of designed geometry with natural patterns. By integrating this optimisation method into the design process, the façade pattern generation can be automated and optimal design can be selected by evaluating multiple design solutions. Instead of using repetitive geometrical patterns or generated pseudo-randomness, patterns objectively similar to those occurring in nature can be created without directly copying natural structures. The distribution of the structural and shading elements controls the way natural light permeates the building and, considering the data gathered from images of natural scenes, this method can be used to design structures not only with optimal structural and energy performance but also with visual and psychological occupant comfort in mind.

Exploration of Modern Design of Traditional Ceramic Patterns Integrating Big Data and CAD Technology

Exploration of Modern Design of Traditional Ceramic Patterns Integrating Big Data and CAD Technology

Effectiveness of a Training Program in Developing Graduates Skills for Pattern Design Using the Gerber System

Effectiveness of a Training Program in Developing Graduates Skills for Pattern Design Using the Gerber System

UMUR SIMPAN TELUR AYAM YANG DILAPISI DENGAN KAPUR (CaCO3) DAN MINYAK KELAPA

Preservation of fresh eggs can be done by coating the centipede with coating material. The purpose of this study was to determine the physical quality of chicken eggs treated with centipede coating and shelf life at room temperature. The ingredients used are purebred chicken eggs, coconut oil and chalk. The parameters observed are: Egg weight, egg index, egg white index, yolk index, egg white pH, yolk pH, egg color. The study design is a complete randomized design of factorial patterns. The results showed that the type of egg centipede coating material and shelf life showed a marked difference in egg weight. The coating material and shelf life have no effect on the egg index. The treatment of centipede coating material has a very noticeable effect on the egg white index and egg yolk index. The treatment of centipede coating material and shelf life have a significant influence on the pH value of egg white and egg yolk pH. The color of the yolk of purebred chickens with the treatment of centipede coating materials and the length of storage at room temperature has a noticeable effect on the color of the yolk. The conclusion that the coating of the egg centipede using chalk and coconut oil and shelf life showed a marked difference in egg weight, egg white index, yolk index, white pH, yolk pH and egg color, while the egg index did not differ markedly.

A research paper on software design patterns

This article affords another exhaustive examination of software design patterns, discussing their importance, the classification system, and the influence on software architecture and design. It looks at how existing practices handle predictable problems, make things more easily serviceable, and increase developer collaboration. The article goes further and explains the use of design patterns and elaborates on real-life examples of design patterns and the difficulties and drawbacks of using them. Further, it expands on future possibilities, such as applying design patterns for cloud-new architectures, AI incorporation, serverless, and Agile/DevOps. From these trends, the article lays down the argument that design patterns are not insulated from change but are continually being adapted to fit into the software development processes of today's complex and sophisticated world and that to be relevant in the designing of today's complex, large and intelligent software-based systems, developers should be familiar with both the recognized and emergent design patterns.

The Analyst’s Hierarchy of Needs: Grounded Design Principles for Tailored Intelligence Analysis Tools

Intelligence analysis involves gathering, analyzing, and interpreting vast amounts of information from diverse sources to generate accurate and timely insights. Tailored tools hold great promise in providing individualized support, enhancing efficiency, and facilitating the identification of crucial intelligence gaps and trends where traditional tools fail. The effectiveness of tailored tools depends on an analyst’s unique needs and motivations, as well as the broader context in which they operate. This paper describes a series of focus discovery exercises that revealed a distinct hierarchy of needs for intelligence analysts. This reflection on the balance between competing needs is of particular value in the context of intelligence analysis, where the compartmentalization required for security can make it difficult to group design patterns in stakeholder values. We hope that this study will enable the development of more effective tools, supporting the well-being and performance of intelligence analysts as well as the organizations they serve.

Framework for Implementation of Building Automation Control Programs for Industrial Heating and Cooling Systems

This article proposes a novel framework for the rapid implementation of automation programs in industrial heating and cooling systems. The global push for sustainability necessitates significant infrastructural transformations within these systems, which currently rely heavily on fossil fuels and are responsible for 75% of industrial final energy consumption. Our research highlights the critical role of design patterns and object-oriented programming principles to address the complex integration of additional energy converters and storage into automation programs. By leveraging design patterns, our framework encapsulates the intricacies of various components, such as actuators, sensors, and storage, within a comprehensive object-oriented model that also allows the integration of different control strategies. Qualitatively, this approach enhances the reusability, scalability, and adaptability of automation programs. Therefore, quantitatively, our framework enables a more resilient and efficient energy system. The framework is validated through its application to a complex, cross-linked industrial heating and cooling system at the ETA Research Factory of the Technical University of Darmstadt. Using the developed framework reduces implementation effort significantly due to its consistent and modular structure resulting from the reusable design patterns.

Microservices Patterns Recommendation based on Information Retrieval

Software developers encounter recurring problems during software development, which can be solved using proven solutions known as design patterns. Microservices architecture, a Service-Oriented Architecture (SOA) variant, presents common communication, deployment, and service definition challenges. However, selecting the appropriate design pattern from a vast pool of patterns to solve a problem is difficult for novice and experienced developers. This paper proposes a recommendation tool based on Information Retrieval (IR) to assist developers in choosing the suitable microservices pattern to solve a given problem. The tool leverages textual descriptions given by developers to provide relevant indications of microservices patterns. It has been evaluated using both toy and industrial problems, demonstrating promising results. The results showed that the tool was able to solve 60% of toy design problems, indicating that it can provide valuable and accurate recommendations. Furthermore, tests with industrial problems revealed that over 70% of the recommended patterns helped to address the problems at hand. Interviews with developers who work in the software industry corroborated the recommendation tool’s effectiveness and practicality.

A Sustainable Vision for Technical Education 4.0 of Post COVID-19

The impacts of industry 4.0 have been reflected in education around the world as countries compete to formulate educational policies based on innovation and digitization in order to adapt to the IR 4.0. In this regard, a new approach to technical education 4.0 has been formulated. It seeks to integrate technical education with the technology developments that define the Industrial Revolution 4.0, emphasizing the importance of this alignment in promoting sustainable economic growth and fostering inclusive development. The paper highlights the strategies and techniques implemented in the design of technical education 4.0 school buildings, arriving at legislative and design recommendations for creating school buildings that are compatible with sustainable education, meet the needs of industry 4.0 building practices, and are supported by modern technologies. By using an integrated approach in terms of new design needs and new education needs that adapt to modern pandemics and prevent any diseases in the future, this research aims to present a new model for technical education 4.0 in the pandemic era in line with the sustainable development goals in the Education Strategy 2030. This study discusses the problems existing in the current situation of technical education schools in Egypt and comes up with a new model that is compatible with new design and educational needs. It is structured using new design strategies for technical education 4.0 schools based on design patterns for 21st century schools that meet industry 4.0 needs and address the COVID-19 pandemic.

Enhancing Personalized Learning Through Process Mining

AbstractTechnology-mediated learning offers new possibilities for individualizing learning processes in order to discover, monitor, and enhance students’ learning activities. However, leveraging such possibilities automatically and at scale with novel technologies raises questions about the design and the analysis of digital learning processes. Process mining hereby becomes a relevant tool to leverage these theorized opportunities. The paper classifies recent literature on individualizing technology-mediated learning and educational process mining into four major concepts (purpose, user, data, and analysis). By clustering and empirically evaluating the use of learner data in expert interviews, the study presents three design patterns for discovering, monitoring, and enhancing students’ learning activities by means of process mining. The paper explains the characteristics of these patterns, analyzes opportunities for digital learning processes, and illustrates the potential value the patterns can create for relevant educational stakeholders. Information systems researchers can use the taxonomy to develop theoretical models to study the effectiveness of process mining and thus enhance the individualization of learning processes. The patterns, in combination with the taxonomy for designing and analyzing digital learning processes, serve as a personal guide to studying, designing, and evaluating the individualization of digital learning at scale.

Generation Method for HVAC Systems Design Schemes in Office Buildings Based on Deep Graph Generative Models

The design process of heating, ventilation, and air conditioning (HVAC) systems is complex and time consuming due to the need to follow design codes. Since the design standards are not fixed, the final outcome often depends on the designer’s experience. The development of building information modeling (BIM) technology has made information throughout the building lifecycle more integrated. BIM-based forward design is now widely used, providing a data foundation for combining HVAC system design with machine learning. This paper proposes an unsupervised learning method based on deep graph generative models to uncover hidden design patterns and optimization strategies from the design results. We trained and validated four deep graph generative models—GAE, GNF, GAN, and diffusion—using HVAC system terminal pipeline layout data. Accuracy and precision metrics were used to compare the generated designs with automated forward design solutions, assessing the models’ ability to capture both local variations and broader changes in design logic. A graph-neural-network-based evaluation method was employed to measure the models’ capacity to detect changes. The results indicate that all four models achieved prediction accuracies exceeding 90% and precision rates above 75%. The models effectively captured both local modifications made by designers and global design changes, showing greater sensitivity to global layout adjustments than to local updates. When comparing the results generated by deep graph generative models and the actual design, it is obvious that the accuracy of the predictions varies significantly due to the complexity of the test buildings.

ViCo: Human visual perception-based contour extraction of Chinese Tang dynasty textile patterns

The study of ancient textile patterns not only enriches historical material but also inspires modern costume art design. Recent developments in computer vision technology provide novel analytical methods for the study of ancient textile patterns. As contours are one of the most significant features in computer vision tasks, contour extraction serves as a prerequisite to accomplishing intelligent understanding and automatic design of textile patterns. In this paper, a perception-consistent contour extraction method (ViCo) that simulates the human visual system from the retina, the lateral geniculate nucleus (LGN), to the V1 area in the cortex is proposed, along with an ancient textile pattern dataset represented by TuanKe in the Chinese Tang dynasty. Experiments were conducted both qualitatively and quantitatively to verify the effectiveness of the proposed method on the TuanKe dataset. Analysis of the results implies the effectiveness of ViCo because the retinal and LGN filter enhances edge information and restrains tiny pixel changes, and the cortex simulation is direction selective. This study is among the initial efforts to employ computer vision technology for ancient textile pattern studies. The study presents a TuanKe dataset and a novel bio-inspired contour extraction method, which has significant historical research importance, fabric art design inspiration, and computer application value.

The Regulation of Temperature Fluctuations and Energy Consumption in Buildings Using Phase Change Material–Gypsum Boards in Summer

This study examined the thermal performance of Comfortboard23, a commercial gypsum board from Knauf infused with phase change material (PCM). Structural characterization using XRD and SEM confirmed the presence of microencapsulated PCM within the gypsum matrix. The study does not provide a direct comparison between Comfortboard23 and other PCM-integrated gypsum boards on the market. This is a limitation of the research. A comprehensive comparison would involve testing multiple products under identical conditions, and evaluating factors such as thermal performance, cost-effectiveness, durability, and ease of installation. Thermal characterization involved a novel low-scale thermal chamber to measure U-value, thermal conductivity, heat storage capacity, and dynamic thermal response. Results showed incorporating PCM decreased the U-value by 2% compared to standard gypsum boards. Additionally, PCM inclusion increased heat storage capacity by around 45% and improved dynamic thermal characteristics by decreasing thermal stability coefficient from 0.92 to 0.76 and increasing thermal lag from 0.27 to 0.49 h. The 45% increase in heat storage capacity of Comfortboard23 could lead to a 10–20% reduction in heating and cooling energy consumption, improved thermal comfort, and potential HVAC downsizing. Exact benefits depend on climate, building design, and occupancy patterns, necessitating further research in diverse real-world settings. The findings demonstrate Comfortboard23’s potential for enhancing thermal energy storage in buildings, contributing to energy savings, improved thermal comfort, and reduced temperature fluctuations across varying daily temperatures. Overall, the study highlights the promise of Comfortboard23 as an energy-efficient PCM-integrated building material.

Comparison Of The Effectiveness Of Grape Seed And Onion Extract In Healing Cut Wounds In Wistar Rats

In healing cut wounds, generally many use drugs with chemicals, the use of chemicals in wound healing has a lot of negative impacts, therefore it is necessary to conduct further research on the benefits of natural ingredients such as plants to treat cut wounds, some of the advantages of using medicinal plants include relatively safer, easy to obtain, cheap, does not cause resistance, and relatively harmless to the surrounding environment or the mixture between the plants, which has been used for treatment for generations. One way to treat cut wounds is to use herbal plants because they are cheaper, easier to get, and have low side effects. Compounds that play a role in the healing process of cut wounds include flavonoids, saponins, tannins, polyphenols, and essential oils. One of the plants that has health benefits is grapes. The purpose of this study is to find out the comparison of the effectiveness of grape seeds and onion extract in healing cut wounds in wistar rats. The type of research used in this study is experimental research with a true experimental method with a post-test only control group design pattern. The sample to be used in this study is 24 rats divided into 4 groups so that each group contains 6 rats. Data analysis uses the One-Way ANOVA test. The results showed that shallot gel extract had a significant effect on the percentage of reduction in incision length.

Efektivitas Serbuk Daun Binahong (Anredera Cordifolia (Ten.) Steenis) terhadap Telur Cacing Haemonchus Sp pada Domba

Worm parasitic diseases are a serious problem in livestock, especially ruminants. This study aims to determine the anthelmintic effectiveness and concentration of Binahong leaf powder (Anredera cordiofolia (Ten.) steenis) on the mortality of Haemonchus sp worm eggs in sheep. This research is an experimental method with a completely randomized design with 1 factor, namely Binahong leaf powder dissolved in water at concentrations of 0 mg/kg, 200 mg/kg, and 250 mg/kg (three concentrations) which will be repeated six times. Observations were made before and after treatment for fourteen days given Binahong leaf powder. Then count the number of dead worm eggs in the feces through a microscope. The data that was obtained was then calculated and analyzed using Anova (Analysis of Variance) with table F using a Completely Randomized Design (CRD) pattern, then continued with the Duncan Test to find out which treatment had the most influence on the death of Haemonchus sp worm eggs. The results of the research showed that various concentrations of Binahong leaf powder as an anthelmintic were able to kill Haemonchus sp worm eggs in sheep feces positively and significantly with a concentration of 250 mg/kg being the concentration that had the highest mortality effect. The active compound content in binahong leaf powder is effective in killing 50% (LC50) of Haemanchus sp worm eggs at a dose of 194.55 mg/kg with a percentage of up to 100%.

Pattern design for capacity building of promoters in climate-smart agriculture environment development

This study aimed to investigate the impact of agricultural environment, organizational, educational, economic, social, technical, cultural, and legal factors on the capacity building of extension experts in the development of climate-smart agriculture. The research is applied in terms of its objective and descriptive-survey in terms of its method. The statistical population of the research consisted of extension experts in three provinces, East Azerbaijan, West Azerbaijan, and Ardabil (N=4256). A sample size of 354 was selected using the Cochran formula. The data collection tool was a questionnaire using a five-point Likert scale. The formal and content validity of the questionnaire was confirmed by a group of experts and using the Average Variance Extracted (AVE) method before conducting the pilot study. The reliability of the research tool was evaluated by conducting a pilot study among 25 individuals outside the statistical population. In this research, SmartPLS software was used for data analysis. The results showed that infrastructural factors had the highest impact on climate-smart agriculture with 22%, followed by organizational factors with 21%, social factors with almost 17%, cultural factors with 16.5%, educational factors with 13%, legal factors with nearly 13%, technical factors with 11.4%, and finally, economic factors with just over 10%. Overall, the factors under study explain more than 68% of the variance in climate-smart agriculture (R2=0.687), indicating the impact of the aforementioned factors on the development of climate-smart agriculture. Also, the design of this model made the promoters, by identifying and increasing the potential and capacities of themselves, villagers and farmers, to be able to adapt themselves to climate change and drought, and by increasing resilience and adaptability, to have positive effects for the development of sustainable agriculture. Along with increasing the product, it will increase the income and reduce the costs for them.

Healthy urban blue space design: Exploring the associations of blue space quality with recreational running and cycling using crowdsourced data

Urban blue space offers substantial health benefits by encouraging population physical activity. Despite much evidence on the nature-health nexus, the relationship between blue space and recreational exercises remains under-studied, limiting the realisation of health benefits in blue space design. Using crowdsourced data, including volunteered geographic information and street view image data, this study investigates the associations of blue space quality with recreational running and cycling in Rotterdam, the Netherlands. Results show that recreational exercise levels on street segments vary based on the blue space type and design. Compared to inland canals and rivers, small-scale recreational waterbodies are more conducive to running but not cycling, while both activities tend to cluster around the Nieuwe Maas River. Interestingly, the Water View Index shows a general negative association with both activities after adjusting for the blue space type. Besides the waterbody characteristics, eye-level environmental factors, including higher Green View Index, lower building density, more diverse land use, greater connected street network and fewer traffic elements, are associated with more running and cycling exercises. Results for visual complexity and neighbourhood population composition are mixed depending on the exercise type. These findings are further translated into spatial design patterns for developing exercise-supportive and health-promoting blue spaces.

Phonon-polariton Bragg generation at the surface of silicon carbide

Phonon-polaritons are known to emerge at the surface of solids under infrared (IR) irradiation at frequencies close to the optical phonon resonance. Metal, patterned on the top of the polariton-active surface, locally blocks the excitation of surface waves due to plasmonic screening and can be used for the design of wave patterns. We excite polaritonic waves at the surface of SiC under the irradiation of a CO2 laser (λ∼10μm) and visualize them using apertureless near-field interference scanning probe microscopy. From the near-field scans in the vicinity of gold film periodical strip structures, we identify the Bragg scattering (diffraction) outside the grating with the contribution from separate strips coherently summed up, provided that the wavelength matching condition is fulfilled. The observed phenomena agree with wavefield calculations. Our observations demonstrate the potential of metal-patterned silicon carbide for the fabrication of on-chip polaritonic IR circuits.

Encodable DNA Hairpin Probes for Nanopore Multiplexed Target Detection.

Owing to the co-occurrence of hazardous compounds, it is crucial to build multiple highly discriminative probe libraries for simultaneous determination. Drawing inspiration from nucleic acid barcodes, we developed a probe system that is exclusively based on the nucleic acid secondary structure's hairpin structure, which can be directly read by nanopores. The highly distinguishable hairpin probes were constructed, and a detailed explanation of the possible patterns in their design was provided. These probe-representative events measured through the α-hemolysin (α-HL) nanopores were both distinguished, either through visual observation or comparison of the nanopore parameters. Besides, the potential design pattern for probes with unique telegraphic switching between the two levels was also unveiled. Finally, these probes were utilized to realize simultaneous, ultrasensitive mycotoxin multiple-detection, and their prospective applications for the detection of proteins and microRNAs were presented, indicating their suitability for a wide range of sensing applications.