Design Patterns Research Articles

Pengaruh Pemberian Red Mud dan Bokasi Limbah Sayur Terhadap Pertumbuhan dan Hasil Selada Hijau pada Tanah Gambut

This research aims to find the best interaction dose of red mud and vegetable waste on the growth and yield of green lettuce plants on peat soil. This research used an experimental method with a Completely Randomized Factorial Design pattern consisting of two factors, each consisting of 3 treatment levels with 3 repetitions and consisting of 4 sample plants so that the total number of plants was 108 plants. The first factor, namely red mud (A) consists of a1 = 18 tonnes/ha equivalent to 220.5 g/plant, a2 = 20 tonnes/ha equivalent to 245 g/plant and a3 = 22 tonnes/ha equivalent to 269.5 g /plant and the second factor consists of b1 = 15 tonnes/ha equivalent to 184 g/plant, b2 = 20 tonnes/ha equivalent to 245 g/plant and b3 = 25 tonnes/ha equivalent to 306 g/plant. Observation variables include: Number of leaves, root volume, plant dry weight and plant fresh weight. Apart from the variables above, observations were also made of environmental conditions which included: soil pH, air temperature, relative humidity and daily rainfall. Based on the research results, it shows that giving 18 tons/ha of red mud is the best dose in increasing the fresh weight of plants and 20 tons/ha of vegetable waste fertilizer is the best dose in providing growth in the number of leaves in the 4th week of green lettuce plants on peat soil. Keywords: vegetable waste bokasi, red mud, green lettuce, peat soil

Characteristics of Hazardous Rock Avalanche Disasters on High and Steep Slopes and Countermeasures for Prevention and Control in Wuling Mountain Area of Chongqing

Chongqing Wuling Mountain area has complex geological conditions and frequent geologic disasters, which bring severe challenges to the construction of highways along the route, especially affected by the topography and meteorological conditions in the Chongqing region, the distribution of disaster points is dense, and the disaster management is difficult. This paper takes a highway in Chongqing Wuling Mountain area as an example, fully analyzes the development characteristics of geologic disasters along the route, and concludes that dangerous rock collapse is a typical geologic disaster on the slope in Chongqing Wuling Mountain area. The influencing factors of dangerous rock failure on the slope are divided into three categories: geological conditions, meteorology and hydrology, and slope design pattern, and their influencing mechanisms are elaborated respectively. Finally, 16 high and steep slopes along the route are analyzed in depth, divided into four grades according to the degree of influence on slope safety, and targeted prevention and control measures are proposed. It can provide certain reference for the construction of highway along the Wuling Mountain area in Chongqing.

Design Patterns in Mixed Methods Research: Embedding Mixed Methods Matched Comparisons Sampling in Previous Design Decisions

Design Patterns in Mixed Methods Research: Embedding Mixed Methods Matched Comparisons Sampling in Previous Design Decisions

An attempt to determine the impact of the implementation of autonomous vehicles on a larger scale on the planning of city transport systems

Purpose: This paper aims to explore the potential impact of autonomous vehicles (AVs) on urban planning, sustainable urban development, and tourism. Methodology: The paper is a conceptual study that reviews and synthesizes existing literature on AVs, urban planning, and tourism. It also uses case studies to illustrate the potential effects of AVs. Results: The widespread adoption of AVs is likely to have significant implications for urban planning, including changes in land use, infrastructure design, and transportation patterns. AVs may also contribute to sustainable urban development by reducing traffic congestion and air pollution. In the tourism sector, AVs could lead to spatial changes, new social inequalities, and changes in the overnight visitor economy. Theoretical contribution: The paper contributes to the understanding of the complex interplay between AVs, urban planning, and tourism. It highlights the need for urban planners and tourism stakeholders to consider the potential impact of AVs in their decision-making processes. Practical implications: The paper provides practical insights for urban planners, tourism stakeholders, and policymakers on how to prepare for and adapt to the widespread use of AVs. It also emphasizes the importance of considering the potential benefits and challenges of AVs in the context of specific cities and tourism destinations.

Rapid profiling rock mass quality underneath tunnel face for Sichuan-Xizang Railway

The Sichuan-Xizang Railway is a global challenge, surpassing other known railway projects in terms of geological and topographical complexity. This paper presents an approach for rapidly profiling rock mass quality underneath tunnel face for the ongoing construction of the Sichuan-Xizang Railway. It adopts the time-series method and carries out the quantitative analysis of the rock mass quality using the depth-series measurement-while-drilling (MWD) data associated with drilling of blastholes. A tunnel face with 15 blastholes is examined for illustration. The results include identification of the boundary of homogeneous geomaterial by plotting the blasthole depth against the net drilling time, as well as quantification of rock mass quality through the recalculation of the new specific energy. The new specific energy profile is compared and highly consistent with laboratory test, manual logging and tunnel seismic prediction results. This consistency can enhance the blasthole pattern design and facilitate the dynamic determination of charge placement and amount. This paper highlights the importance of digital monitoring during blasthole drilling for rapidly profiling rock mass quality underneath and ahead of tunnel face. It upgrades the MWD technique for rapid profiling rock mass quality in drilling and blasting tunnels.

Design patterns for the construction of computational biological models.

Computational biological models have proven to be an invaluable tool for understanding and predicting the behaviour of many biological systems. While it may not be too challenging for experienced researchers to construct such models from scratch, it is not a straightforward task for early stage researchers. Design patterns are well-known techniques widely applied in software engineering as they provide a set of typical solutions to common problems in software design. In this paper, we collect and discuss common patterns that are usually used during the construction and execution of computational biological models. We adopt Petri nets as a modelling language to provide a visual illustration of each pattern; however, the ideas presented in this paper can also be implemented using other modelling formalisms. We provide two case studies for illustration purposes and show how these models can be built up from the presented smaller modules. We hope that the ideas discussed in this paper will help many researchers in building their own future models.

A closed-loop human-computer interactive design method based on sequential human intention prediction and knowledge recommendation

Designers working on large-scale complex engineering projects may encounter design errors due to limited experience and expertise. Therefore, during the design process, accurately identifying the designer’s design intention and recommending relevant design knowledge can enhance design efficiency and reduce errors. In this paper, we propose a closed-loop human–computer interactive design method based on sequential human intention prediction and knowledge recommendation. This method leverages the Function-Behaviour-Structure (FBS) model to reduce the dimensionality of design action sequences, so as to facilitate the analysis of potential design patterns. The processed action sequences are used to train Transformer to predict design intentions. In different input sequences, Transformer achieved a highest prediction accuracy of 92.09%. We construct a Design Knowledge Recommendation Framework (DKRF) and its corresponding design knowledge matching algorithm. This framework accurately recommends design knowledge to designers, solving design stagnation and improving design efficiency. Finally, a case study of four types of mechanical model design is conducted to demonstrate the feasibility and wide applicability of the proposed closed-loop human–computer interactive design method.

Advanced Liquid-Metal-Cooled Fast Reactor Core Design Using Modern Optimization Algorithms

When performing core loading pattern design in fast spectrum reactors, it is often assumed that the larger neutron mean free path in fast reactors makes the core loading pattern less significant than in thermal reactors. Due to this assumption, the literature often includes homogeneous core designs for liquid-metal-cooled fast reactors (LMFRs). In this paper, heterogeneous loading patterns are investigated using modern LMFR multiphysics analysis. It was found that the figures of merit (FOMs) used to design cores are very sensitive to the core loading pattern, and better core designs (measured by the FOM) can be obtained from heterogeneous designs. Based on this investigation, a need for a modern LMFR core loading pattern design methodology is identified and developed. The methodology is demonstrated through the optimization of the core loading pattern of a sodium-cooled fast reactor. The reactor design used in this demonstration is based on the Super Power Reactor Innovative Small Modular (SPRISM) core, and an optimized loading pattern is obtained by searching for the fuel enrichment and locations of the driver and blanket assemblies. The objectives of the search are to reduce the fuel cost and peaking factors, while meeting the design constraints. To calculate the fuel cost, a preliminary cost model is developed and applied for transuranium fuel loading. Upon establishing the methodology, six optimization algorithms are tested for their effectiveness in solving the LMFR core loading pattern problem. Four of the algorithms are population based: Gray Wolf Optimization, Salp Swarm Optimization, Whale Optimization Algorithm, and the Moth Flame Optimization. A reinforcement learning algorithm, called the proximal policy optimization, was also selected. Finally, the differential evolution (DE) algorithm was selected as the choice of an evolutionary-based algorithm. All algorithms showed a competitive converged design. However, the DE showed more favorable performance since it was able to converge to a superior design compared to the rest of the algorithms with a reasonable number of design sample evaluations, in addition to avoiding local minima entrapment.

Empowering Large Language Models in Hybrid Intelligence Systems through Data-Centric Process Models

Hybrid intelligence systems aim to leverage synergies in closely collaborating teams of humans and artificial intelligence (AI). To guide the realization of such teams, recent research proposed design patterns that capture role-based knowledge on human-AI collaborations. Building on these patterns requires hybrid intelligence systems to provide mechanisms that orchestrate human and AI contributions accordingly. So far, it is unclear if such mechanisms can be provided based on shared representations of the required knowledge. In this regard, we expect ontology-based data-centric process modeling to be a promising direction for hybrid intelligence systems that aim to support knowledge-intensive processes (KiPs). We illustrate this through exemplary process models (realized with our ontology- and data-driven business process model -- ODD-BP) that reflect the team design patterns for hybrid intelligence systems. We point out that relying on such process models enables multiple actors to fulfill roles jointly and allows them to address individual shortcomings. This is examined by discussing integrating large language models (LLMs) into the process models and describing how complementary AI actors could help to empower LLMs to fulfill their role in human-AI collaboration more comprehensively. Future work will extend the provided concepts while their evaluation initially focuses on the KiP of medical emergency call handling.

An Aesthetic Emotion Model for Chinese Ming-Style Furniture Patterns

Ming-style furniture patterns hold significant cultural importance within traditional Chinese heritage. Despite being frequently integrated into modern Chinese product design, a comprehensive scientific investigation into the psychological framework governing people's appreciation of these patterns has been lacking. Therefore, this article employs structural equation modeling analysis to delve into the aesthetic structure of Ming-style furniture patterns. The results found that: (1) Emotion, as the dependent variable, is influenced by perceptual and cognitive factors, with familiarity being the most crucial influencing indicator. (2) The model proposed in this article exhibited no variations across age and gender groups, but did demonstrate differences based on individual expertise. These research findings not only bridge the void in empirical studies on the aesthetics of Chinese traditional patterns but also establish a theoretical foundation for enhancing the decorative impact of traditional patterns in product design.

Study on the solder flow in a narrow gap with metal surface texture

Obvious voids in the solder in a narrow gap is a common problem that greatly affects the reliability of mechanical connections. Due to its high heating rate, laser soldering causes more severe voids and even evolves into dispersion of the solder. A method of metal surface texturing is put forward, in which the texture gradient is used to directionally transport solder for lower dispersity, and the pattern design of texture is used to reduce the void rate. The directional transport of solder is realized through the differences in oxidation degree and microstructure of stainless steel surface under different ultrafast laser scanning speeds. The discharge of voids in the solder is achieved through the reservation of the central area in the solder and the oscillation during the laser heating process. Based on the present method, the aggregation of solder is achieved, with the void rate of 18 % and the joining strength of 10.4 MPa.

Legal Design Patterns: New Tools for Analysis and Translations Between Law and Technology

Design patterns, a concept originated in urban architecture and adopted also in software engineering, provides a potential approach also for translations between law and technology. This approach will be examined and elaborated from various viewpoints in this topical collection, for which this introductory article provides an overall framework. Here, we discuss design patterns as documentations of living practice, which embed legal concepts, rules, and thinking and between internal and external perspectives to law. We argue that design patterns provide a structured format for interdisciplinary discussions and enhance problem-solving and self-reflecting capabilities of legal scholarship.

Evaluating the impact of bird collision prevention glazing patterns on window views

Optimal design of bird collisions prevention glazing patterns is pivotal in the protection of avian ecology and provision of quality window views for building occupants. However, a research gap currently exists regarding the impact of different pattern designs on the quality of window views. Therefore, this study evaluates the influence of various bird collision prevention pattern designs on window view clarity. A total of 18 patterns, including dot matrix, vertical stripes, and horizontal stripes, were designed and evaluated. The patterns had varying combinations of coverage rates and spacing ratios. Sixty participants were recruited to participate in an experimental survey using virtual reality (VR) technology. They were asked to rate the level of clarity of window views observed through different glazing pattern designs. The results indicated that the bird collision prevention glazing pattern designs significantly influenced occupants’ perception of visual clarity. Designs featuring horizontal and vertical stripes attained higher visual clarity ratings compared to the dot matrix pattern. Additionally, visual clarity significantly decreased with increasing coverage rates and designs with larger spacing ratios were associated with higher clarity than smaller spacing ratios. Most participants were willing to sacrifice window view quality in order to minimize bird fatalities. These findings can guide the development of window view evaluation criteria in existing green building standards, by accounting for the trade-off between avian conservation and window view clarity.

Mathematical Modeling and Design of Parboiled Paddy-Impinging Stream Dryer Using the CFD-DEM Model.

Impinging stream dryers (ISDs) are effective for removing moisture from particulate materials because of the complex multiphase transport of air particles in ISDs. Nowadays, computational techniques are powerful to simulate multiphase flows, including dilute and dense-phase gas-solid flows and hence, the use of a reliable computational model to simulate the phenomena and design a dryer has recently received more attention. In this study, computational fluid dynamics, combined with the discrete element method (CFD-DEM) and falling drying rate model, were used to predict the multiphase transport phenomena of parboiled paddy in a coaxial ISD. The design of an impinging stream pattern for improving residence time in a drying chamber of ISD was also investigated. The results showed that the CFD-DEM, in combination with the falling drying model, could be well-utilized to predict the particle motion behavior and lead to more physically realistic results. The predicted change of moisture content in parboiled paddy was in good agreement with the experimental data for 17 cycles of drying. Although the prediction of mean residence time was lower than the experimental data, the predicted mean residence time was a similar trend to the experimental data. For ISD design, the simulation revealed that the use of two stages of impinging stream region (two streams collide at the top of the drying chamber at the first stage and then the gas particles flow on the incline floor to collide with the other stream at second stage) in a drying chamber could increase the residence time approximately 75% and reduce drying cycle from 17 to 10 cycles when it was considered at the same final moisture content.

Optimization design of custom pattern based on microclimate heat transfer

Highlights3D air gap distributions.Heat transfer varies with air gap distance.Thermal comfort can be improved by optimizing garment pattern.

A large-scale machine learning analysis of inorganic nanoparticles in preclinical cancer research.

Owing to their distinct physical and chemical properties, inorganic nanoparticles (NPs) have shown promising results in preclinical cancer therapy, but designing and engineering them for effective therapeutic purposes remains a challenge. Although a comprehensive database of inorganic NP research is not currently available, it is crucial for developing effective cancer therapies. In this context, machine learning (ML) has emerged as a transformative tool, but its adaptation to nanomedicine is hindered by inexistent or small datasets. Here we assembled a large database of inorganic NPs, comprising experimental datasets from 745 preclinical studies in cancer nanomedicine. Using descriptive statistics and explainable ML models we mined this database to gain knowledge of inorganic NP design patterns and inform future NP research for cancer treatment. Our analyses suggest that NP shape and therapy type are prominent features in determining in vivo efficacy, measured as a percentage of tumour reduction. Moreover, our database provides a large-scale open-access resource for discriminative ML that the broader nanotechnology community can utilize. Our work blueprints data mining for translational cancer research and offers evidence for standardizing NP reporting to accelerate and de-risk inorganic NP-based drug delivery, which may help to improve patient outcomes in clinical settings.

Implementation of a Universal Framework Using Design Patterns for Application Development on Microcontrollers.

This article focuses on the area of software development for microcontrollers and details the implementation of modern programming practices and principles in embedded systems and IoT applications. This article explains how we implemented previously unimplemented principles and applied design patterns for quality software design on microcontrollers, which are currently only used for developing applications on the higher layers of the IoT reference model. A custom modular framework for microcontrollers is presented, based on applying SOLID principles and adapting design patterns specific to the microcontrollers' application development needs. The implemented framework enables independent communication between modules and flexible integration of hardware components. It is designed with platform independence in mind, contributing to its wide adaptability and ease of use in diverse development environments. By applying these technological approaches, we can create applications that are not only testable and extensible in terms of application logic but also allow for easy adaptation to changes in these hardware resources. Utilizing these capabilities represents an innovative approach to development for microcontrollers that fundamentally improves the long-term sustainability and scalability of applications.

The Way to Ignite Creativity: An Overview of Patterns in Interdisciplinary Curriculum

The increasing demand for innovative talents in society has led to a focus on cultivating people who are socially connected and can work both within and outside their discipline. An interdisciplinary curriculum is an innovative way of learning and teaching, aiming to help students improve their creativity. Studies have shown that high school students who employ interdisciplinary or integrated methods achieve better academic performance than those who do not. However, few ways about interdisciplinary curriculum direction and supporting true fusion of disciplines have been understood by teachers or teaching administrators. This thesis uses documentation methods, including text analysis and comparative studies, to analyze patterns in interdisciplinary curriculum design and propose appropriate scenarios using these patterns. In the thesis, the patterns have been divided into four catalogues standard basis, concept basis problem basis and project basis. The study aims to shape common key points that are more concrete, understandable, and actionable for future research in interdisciplinary curricula.

Frequency selective asymmetric coupled-fed (ACS) antenna using additive manufacturing

In this study, the development of diverse antenna designs using additive manufacturing processes, specifically spanning from L-band to K-band is proposed. All designs are implemented on a flexible FR4 substrate to make them suitable for wearable sensors and biomedical applications. The fabrication process involves the utilization of aerosol jet printing with nanoparticle silver ink, followed by curing in a vacuum chamber. Additionally, screen printing with copper paste is employed as another method, with subsequent curing in a laminator. The reflection coefficient (S11) and radiation patterns for the simulated design and fabricated samples were found to align closely. The achieved return loss consistently reaching −10 dB across fairly large operating frequency range underscores the efficacy of the proposed antennas and their associated additive manufacturing mechanisms. The design and simulation were performed using Ansys high frequency structural simulator (HFSS), and the parameters under test for the fabricated antennas were validated using a vector network analyzer (VNA) to assess overall performance.

Exploring the Impact of Campus Landscape Visual Elements Combination on Short-Term Stress Relief among College Students: A Case from China

Although the effect of campus landscape space on stress relief among college students has been confirmed, few existing studies have considered the impact on stress recovery from the perspective of factor combination, and the key visual elements and the most effective combination of visual elements to relieve stress are still unclear. This study attempts to conduct a natural experiment within Chinese campuses, measuring physiological indicators of stress such as heart rate (HR), frequency domain index of heart rate variability (LF/HF), skin conductance level (SCL), skin temperature (SKT), and respiratory rate (RESP) using physiological instruments. It explored the effects of visual elements and their combinations in campus landscape spaces on short-term stress relief among college students through semantic segmentation, multifactorial analysis of variance, and post hoc multiple comparison methods. Research results demonstrate that the presence of water elements in the field of vision can effectively improve the stress relief effects of landscape spaces. Reasonable combinations of natural landscape elements and artificial landscape elements in the design can also effectively promote stress relief among students. Building facade area and sky area, water area and sky area, and plant species and pavement area are three combinations of factors with the strongest interactive effects. “Natural water scenery” and “exquisite artificial” are two campus landscape design patterns most conducive to short-term stress relief.