Design Model Research Articles

A Professional Development Program in Management of Midwifery Emergencies for Midwifery Graduates.

Midwifery emergencies can be managed by providing effective and quality care through a skilled workforce. Improving the quality of midwifery care requires the professional development of midwives, especially those who are novice, to maintain their capabilities and enhance their performance. This study was designed to develop a professional development program in the management of midwifery emergencies for midwifery graduates. This mixed-method study was conducted in two phases. In the first phase, a qualitative study was conducted to investigate the program needs, facilitators, and barriers to the management of midwifery emergencies in midwifery graduates. Further, the initial version of the program was developed based on the results of the qualitative study and literature review. The Analysis, Design, Development, Implementation, and Evaluation (ADDIE) model was used to develop a professional development program for the management of midwifery emergencies. The developed program was then evaluated and approved by a panel of experts. In the second phase, the developed professional development program is implemented, and its impacts are evaluated. Finally, the final professional development program in the management of midwifery emergencies for midwifery graduates is provided. In total, 2,360 primary codes were extracted and merged into 210 codes. After extracting the sub-categories and categories, a review of the texts was conducted, and the final program was developed. Using a professional development program for newly graduated midwives is an effort to improve the health of mothers and infants who receive these services.

Broadband metamaterial linear polarization converter designed by a hybrid neural network with data augmentation

Deep learning techniques provide a new approach to the design and optimization of electromagnetic metamaterials. This study used a convolutional neural network and long short-term memory (CNN–LSTM) hybrid network to design and optimize a broadband metamaterial reflective linear polarization converter. The data augmentation method was also employed in few-shot learning to reduce optimization costs and improve model prediction performance. With the inverse prediction, a linear polarization converter that perfectly covers the Ku-band was obtained and fabricated with flexible printed circuit technology. Both simulation and experimental results indicate that this network can accurately predict the structural parameters. The polarization converter not only achieves remarkable broadband polarization conversion efficiency spanning the 2.2–18 GHz range but also maintains precise cross-polarization control across the entire Ku-band. The mean polarization conversion ratio in the Ku-band was calculated to be an impressive 99.69%. Finally, the mechanism of polarization conversion and the influence of each structural parameter on its performance further verify the optimality of the inverse design model. The use of CNN–LSTM deep learning methods significantly simplified the design process of electromagnetic metamaterials, reducing design costs while ensuring high design precision and excellent performance.

The synergistic effect of artificial intelligence technology in the evolution of visual communication of new media art

This study aims to clarify the synergistic effect of artificial intelligence (AI) technology in the evolution of visual communication of new media art, thereby exploring an AI layout design method based on Convolutional Neural Network (CNN) in the practice of visual communication design. Firstly, this study designs an AI layout design model based on CNN, and trains and optimizes it with training data. Secondly, the automatic generation of layout design is realized by constantly adjusting the model parameters and network structure. Finally, various AI layout design algorithms are compared, and their effects and performances in layout design generation are analyzed. To verify the layout and composition matching model's performance, traditional layout design methods are selected for comparison (layout, comparison, harmonic composition, etc.). This study involved 20 design students as participants, evaluating them across three dimensions: overall comprehensive assessment, readability of text information, and rationality of visual path using a Likert 7-point scale. The results reveal that the proposed method's evaluation outcomes in these three aspects are 5.95, 5.68, and 5.74, respectively, higher than the traditional layout design methods. To sum up, the generative AI discussed here can automatically generate design elements and schemes through deep learning and big data analysis, thus providing a reference for the innovation of visual communication design.

Techno-enviro-economic analysis of grid-connected solar powered floating PV water pumping system for farmland applications: A numerical design model

To meet the required load of a farm in the rural area in Mafraq, Jordan, the complete floating photovoltaic (FPV) water pumping sizing, modelling, and optimization of an on-grid PV system with comprehensive capacity, energy output cost, and emission estimations are outlined in this work. The novelty of this study lies in its comprehensive approach that integrates technical, environmental, and economic factors into a unified framework for designing a PV water pumping system, particularly in scenarios where grid supply is feasible or economically viable. A proposal has been made to install PV panels over the water lake to improve the overall system efficiency and to give an aesthetic appearance. The proposed system is composed of a 165 kW PV array and three 55 kW inverters, which cost 54696.92 JD as the initial cost, CO2 emission reduction of more than 5000 tons and produce electricity at 0.028 JD/kWh. The results indicated that the FPV option demonstrates an about 5 % increase in efficiency compared to the other two scenarios. Also, the FPV option has higher costs due to a 25 % increase in system cost but results in lower CO2 emissions compared to the other two options. Top of Form As shown from the results, the two sizing methods for solar water pumping systems, the equations-based method, and the PVsyst simulation tool give the same results. By following this methodology, one can assess the load, size the system, simulate its operation, and analyse the expected performance. Furthermore, the findings of this study could be valuable in designing a grid-connected FPV water pumping system.

Research on energy consumption evaluation and energy-saving design of cranes in service based on structure-mechanism coupling

Aiming at the problem that the life cycle energy consumption index of hoisting machinery is difficult to be objectively quantified, a crane energy consumption evaluation calculation method based on the working cycle of the service period is proposed, the typical service working mode of the crane is analyzed, and the working cycle process of the mechanism is clarified. On this basis, the stress cycle characteristics of the crane structure during the service period are determined based on the coupling relationship between the mechanism and the structure, which lays the foundation for accurately evaluating the life index of the crane. According to the relationship between the load rate and effective power of each mechanism during the service period of the crane, the calculation method for the evaluation and calculation of the structure energy consumption during the service period of the crane is studied. Finally, the crane is designed based on the concept of absolute service safety, and an optimal design model of the main girder structure of the crane with the goal of the lowest energy consumption in service is established. Using the research method of this paper to study a certain type of bridge crane, the energy consumption of the hoisting machinery during its service period is not only related to the accumulation of the operating characteristics of the mechanism but also related to the characteristic parameters such as the structure self-weight. The comprehensive evaluation of energy consumption provides an effective quantitative method and a reliable green design theory for crane design.

Concurrent topology optimization of sandwich structures with multi-configuration and variable-diameter lattice infill

The superior stiffness-to-weight and strength-to-weight mechanical advantages of sandwich structures can be fully exploited through concurrent design of entire topology, infill configuration and density, where the high-performance yet complicated structure can be fabricated through additive manufacturing. However, the emerging design challenges are concurrent design updating related to sandwich topology, infill configuration and density, which is a design problem with continuous and discrete variables mathematically. In this paper, a concurrent topology optimization is proposed for sandwich structures with multi-configuration and variable-diameter lattice infill. Three design variable fields are employed to describe the fundamental topology considering sandwich structural topology, infill configuration and density simultaneously. Corresponding material interpolation model is developed by combining DSP-based shell-infill description and multi-response latent-variable surrogate model based effective material property calculation. Two-stage design model is formulated as a rough design model considering all design variables followed by a refined design model with only infill density variables, which is developed to strictly satisfy the material allowance constraint due to the mapping between discrete infill configuration variables and continuous latent configuration variables. Corresponding sensitivities of compliance and constraint with respect to the structural topology, infill configuration and density variables are derived, and the method of moving asymptotes (MMA) is employed to solve the design model efficiently. Several numerical examples are presented to systematically demonstrate the effectiveness of the proposed approach.

Development of a competency-based curriculum design model focused on QF(Qualification Framework)

Development of a competency-based curriculum design model focused on QF(Qualification Framework)

Fire resistance of square double-skin concrete-filled steel tubular columns and concrete-filled double steel tubular columns

Square double-skin concrete-filled steel tubular (DSCFST) columns and concrete-filled double steel (CFDST) columns possess excellent load-carrying capacity and ductility. However, there has been limited research on the responses of DSCFST and square CFDST columns exposed to fire. This paper presents a series of tests on such columns loaded concentrically to determine the effects of the steel tube thickness, the strength of materials, load ratio, and boundary conditions on their fire resistance. Additionally, finite element (FE) models are established using ABAQUS, in which the concrete’s transient creep strain is considered through the development of the user-subroutine UEXPAN. A parametric study is undertaken by simulating 156 FE models to further study the behavior of DSCFST and CFDST columns under fire exposure. The fire test and numerical results suggest that both the load ratio and strengths of the internal tube and concrete core play significant roles in determining the fire resistance of DSCFST and CFDST columns. The developed FE models are demonstrated to capture well the fire behavior of loaded DSCFST and CFDST columns. The proposed design model predicts the ultimate loads of DSCFST columns with good accuracy; therefore, it can be employed in the practical design of DSCFST columns.

A Space of Choice: Exploring New Patterns of Common Student Spaces

The paper describes a project conducted by a group of architecture students at the Cracow University of Technology. The research problem focused on common spaces in the learning environment, employing the theoretical framework of the sociology of architecture and the participatory design methodology. The project aimed to propose current design model solutions for inclusive and universally-accessible student places, reflecting on the initial studies and the design workshop experiences. The socio-spatial patterns proposed in this study were inspired by the concept of a pattern language developed by the team led by Christopher Alexander in the 1970s. In contrast to the original patterns, the new proposals for patterns of common student spaces are not statements, but questions. The answers to these questions involve different relationships between individuals (users) and the built environment, including those connecting users to the architectural work, the natural environment, other individuals, or user groups.

Business Model of Insurance Technology Company in Indonesia (Case Study on Premiro.com)

The rapid increase in internet usage in Indonesia has fueled the rise of Insurtech, addressing low literacy, inclusion, and insurance penetration levels. Insurtech companies are pivotal in offering digital-based insurance services to increase insurance users. This research examines the business models employed by Indonesian Insurtech firms, focusing on a case study of Premiro.com. The study also aims to identify the strengths that provide these companies with competitive advantages. Utilizing a descriptive research methodology and a qualitative approach, the research includes interviews and secondary data collection through literature reviews and company information. The analysis employs the Business Model Canvas and Value Design Model frameworks. The study details Premiro's business model elements: customer segments, value proposition, channels, customer relationships, revenue streams, key resources, key activities, key partnerships, and cost structure. It also examines value drivers, nodes, exchanges, and extracts. Findings reveal Premiro's strength lies in its lean and efficient cost structure. The study offers practical recommendations for Premiro to enhance operational effectiveness, expand market share, and boost competitiveness.

Growth Performance, Carcass Characteristics, Immune Response and Meat Quality of Broiler Chickens Fed Muntingia Calabura Leaf Extract

This experiment was carried out to determine the effect of feeding Muntingia calabura leaf extract on the growth performance, carcass characteristics, immune response and meat quality of broiler chickens. 500 1-day old broiler chicks (Cobb 500) were randomly distributed into five treatments of five replicates consisting of ten birds each in a completely randomized design model. Birds in treatment one (control) was fed basal diet alone which is adequate in all nutrients according to the recommendation of broilers while treatment two, three, four and five were fed same diet with Muntingia calabura leaf extract at 0.3 mL, 0.6 mL, 0.9 mL and 1.2 mL per liter of water correspondingly. The duration of the experiment was 56 days and birds had unrestricted access to feed and fresh water. Body weight gain was higher in birds fed treatment four (2555.3 g) and five (2646.1 g), intermediate in treatment two (2346.6 g) and three (2365.1 g) and lower in treatment one (1948.8 g) (P<0.05). Total feed intake and dressing percentage was higher among birds fed Muntingia calabura leaf extract relative to the control (P<0.05). Conversely, mortality of 2.5 % was recorded in control followed by treatment two with 1.00 % none was recorded in the other treatment (P<0.05). Results on the breast muscle revealed that saturated and unsaturated fatty acid was 29.80 %, 41.83 % in control, treatment two (28.11 %, 55.94 %), three (27.19 %, 56.97 %), four (23.15 %, 73.69 %) and five (22.90 %, 73.74 %) in each case (P<0.05). Immunoglobulin A, G and M values were influenced (P<0.05) by the treatments. In conclusion, feeding Muntingia calabura leaf extract up to 1.2 mL/liter of water had no negative effect on the performance and health status of birds.

THIẾT KẾ HOẠT ĐỘNG HỌC TẬP MÔN TIN HỌC CHO HỌC SINH TIỂU HỌC SỬ DỤNG MÔ HÌNH 21CLD ĐỂ PHÁT TRIỂN NĂNG LỰC GIAO TIẾP VÀ HỢP TÁC

Communication and collaboration competency is one of three core general competencies specified in the 2018 Vietnam General Education Curriculum. However, teachers encounter difficulties in designing appropriate learning activities and assessing the development of communication and collaboration skills to cultivate this competency. The 21st Century Learning Design (21CLD) model, proposed by Microsoft, is a teaching framework aimed at developing essential skills in students, including communication and collaboration. This study compared the 21CLD model with the common and core competency framework specified in Vietnam's 2018 General Education Curriculum and found similarities between the two assessment frameworks. Therefore, this article will present Microsoft's 21CLD model, detailing assessment levels according to specific criteria for each skill, and propose a process for applying this model to develop learning activities for Informatics at the elementary level to enhance students' communication and collaboration competency. Keywords: 21CLD; learning design; communication and collaboration; teaching Informatics; primary education.

Design Model for Yoga Industry Development in Indonesia

Design Model for Yoga Industry Development in Indonesia

Ambient temperature and the risk of childhood epilepsy hospitalizations: Potentially neglected risk of temperature extremes and modifying effects of air pollution

PurposeExtreme temperatures and air pollution are increasingly important risk factors for human health in the background of climate change, with limited evidence available for neurological disorders. This study intended to investigate the short-term effects of extreme temperatures on childhood epilepsy and explore the potential modifying effect of air pollution. MethodsDaily childhood epilepsy hospitalization, meteorological and air pollution data were collected from 10 cities in Anhui Province of China during 2016–2018. We firstly employed a space–time-stratified case-crossover design and conditional logistic regression model to fit the short-term relationship between temperature and epilepsy. Then, we conducted stratified analyses by the level of air pollution and individual characteristics. ResultsBoth extreme heat and extreme cold increased the risk of hospitalization for childhood epilepsy. The effect of extreme heat [97.5th vs. minimum hospitalization temperature (MHT)] on hospitalization was acute and emerged at lag0 [OR: 1.229 (95 %CI: 1.035 to 1.459)], while the effect of extreme cold (2.5th vs. MHT) was delayed and appeared at lag5 [OR: 1.098 (95 %CI: 1.043 to 1.156)]. We also found children aged 6–18 years were more susceptible to extreme cold than children aged 0–5 years. Besides, extreme heat and cold effects differed by the level of air pollutants. ConclusionThis study suggests that extreme temperatures might be the novel but currently neglected risk factor for childhood epilepsy, and air pollution could further amplify the adverse effect of temperature.

Interactive Design Model in Computer-Aided Environmental Teaching and Learning

Interactive Design Model in Computer-Aided Environmental Teaching and Learning

Study on a nonlinear dynamic characteristic of the positive flow pump in its pilot hydraulic cylinder

The displacement of the positive flow pump is controlled by its pilot hydraulic cylinder. The tracking performance of the pump displacement directly affects the energy saving of the hydraulic excavator through power matching. In this article, a nonlinear dynamic characteristic of the positive flow pump in its pilot hydraulic cylinder is studied to improve the mathematical model for controller design. The concept of relative water hammer is first proposed to describe the relative pressure wave acting on the hydraulic piston to illustrate the mechanism of the nonlinearity. Chaotic motion can be generated by the relative water hammer when the hydraulic piston is in a partial stroke. The mathematical model is derived and its critical parameters are analyzed. The simulation and experimental results verify the existence of the relative water hammer and the effect of each critical parameter on the pilot hydraulic cylinder and the positive flow pump.

Transition towards net zero emissions: Integration of a PV/T system with a hydroelectric generator and the impact of demand-side management

With the aim of diversifying different energy sources and achieving net zero emissions, hybrid renewable energy sources (HRES) represent the future of the world. However, several HRES simulation software do not integrate the Photovoltaic/thermal (PV/T) system. This article designs an optimal design model for a tri-hybrid Photovoltaic/thermal/hydroelectric (PV/T/H) system for a rural locality in the North Cameroon region. The two Demand Side Management (DSM) strategies used reveal that the DSM strategy significantly reduced the energy cost by 59 % and the emission by CO2 22 % compared to the No-DSM mode. Although the use of battery storage (BSS) is used in both cases, the optimal solutions obtained thanks to the multi-objective optimization method implemented on Matlab led to 418 PV/T panels, 2 MH generators, 2 diesel generators (DG) and 217 PV/T panels and 1 DG for DSM and No-DSM mode respectively. This study is a demonstration of the effect of dynamic tariffs and active demand management technologies on PV/T/H modeling and optimization. It also reveals the need to hybridize PV/T with other energy systems to increase performance and achieve net zero emissions.

Active learning-based machine learning approach for enhancing environmental sustainability in green building energy consumption

Green building (GB) techniques are essential for reducing energy waste in the construction sector, which accounts for almost 40% of global energy consumption. Despite their importance, challenges such as occupant behavior and energy management gaps often result in GBs consuming up to 2.5 times more energy than intended. To address this, Building Automation Systems (BAS) play a crucial role in enhancing energy efficiency. This research develops a predictive model for GB design using machine learning to minimize energy consumption and improve indoor sustainability. The dataset is utilized to predict cooling and heating individually, with data visualization by graphically illustrating dataset features and preprocessing through Z-Score normalization and dataset splitting. The proposed model, based on active learning and utilizing ML regressors such as Random Forest (RF), Decision Tree (DT), Gradient Boosting (GB), Extreme Gradient Boosting (XGBoost), CatBoost (CB), Light Gradient Boosting Machine (LGBM), K-Nearest Neighbor (KNN), and Logistic Regressor (LR), shows significant performance improvements. The CBR-AL model achieves impressive results with values of 0.9975 for cooling (Y1) and 0.9883 for heating (Y2), indicating a high level of accuracy. The model’s success in reducing energy consumption and improving sustainability has potential ripple effects, including substantial cost savings, reduced carbon footprints, and improved operational efficiency in green buildings. This approach not only enhances environmental sustainability but also sets a benchmark for future advancements in predictive modelling for energy management.

Antibody-SGM, a Score-Based Generative Model for Antibody Heavy-Chain Design.

Traditional computational methods for antibody design involved random mutagenesis followed by energy function assessment for candidate selection. Recently, diffusion models have garnered considerable attention as cutting-edge generative models, lauded for their remarkable performance. However, these methods often focus solely on the backbone or sequence, resulting in the incomplete depiction of the overall structure and necessitating additional techniques to predict the missing component. This study presents Antibody-SGM, an innovative joint structure-sequence diffusion model that addresses the limitations of existing protein backbone generation models. Unlike previous models, Antibody-SGM successfully integrates sequence-specific attributes and functional properties into the generation process. Our methodology generates full-atom native-like antibody heavy chains by refining the generation to create valid pairs of sequences and structures, starting with random sequences and structural properties. The versatility of our method is demonstrated through various applications, including the design of full-atom antibodies, antigen-specific CDR design, antibody heavy chains optimization, validation with Alphafold3, and the identification of crucial antibody sequences and structural features. Antibody-SGM also optimizes protein function through active inpainting learning, allowing simultaneous sequence and structure optimization. These improvements demonstrate the promise of our strategy for protein engineering and significantly increase the power of protein design models.

Development of Digital Learning Simulators to Increase Vocational Students' Prior Knowledge

Vocational high schools, receive special attention from the government to produce graduates who are skilled and in line with the demands of the 21st century. The COVID-19 pandemic has disrupted the education system, necessitating a shift from offline to online learning methods. This research focuses on developing digital simulator learning (DSL) media to improve the prior or initial knowledge and problem-solving skills of vocational school students in the field of motorcycle engineering and business. The novelty of DSL media is that students not only learn through the reading process but can also see visually through the simulation process, and also simulate troubleshooting on vehicles. This study follows the analysis, design, development, implementation, and evaluation (ADDIE) model. The research results found that smartphone-based DSL media affected increasing competence in initial knowledge of injection systems, while the effectiveness of DSL media was at a medium level.