Design Evaluation Method Research Articles

Chatbots: The Future of Education?

Chatbots are emerging technologies with the potential to improve teaching and learning processes. This paper conducts a systematic review of research on chatbots in education, focusing on articles published in Online-Journals.org from 2011 to 2024. The aim is to examine the various aspects addressed by the authors, such as design principles, pedagogical roles, interaction styles, and evaluation methods for chatbots in educational contexts. The tools were classified according to the type of user they targeted, revealing that 42% were aimed at students, 11% at teachers, 29% at both types of users, and 18% at external users. The characteristics of the tools along the above dimensions were analyzed, highlighting trends, good practices, and observed limitations. The key findings, challenges, and implications of using chatbots to improve learning outcomes, and experiences were discussed. It was concluded that chatbots are an emerging technology that offers benefits such as teaching personalization, self-learning, and real-time feedback but also poses challenges, such as evaluation and research into their effectiveness for education.

The Application of Augmented Reality in Simulation-Based Design Evaluations of Trauma Rooms.

This study examined the augmented reality (AR) application in design evaluations through an immersive experience of medical task simulations in combination with a full-scale physical mock-up of a trauma room. Augmented reality technology is emerging in various fields including architectural design. Traditionally, building physical mock-ups has been the most effective tool to involve end-users in design evaluations. However, AR can eliminate cost- and labor-intensive components of a physical mock-up by replacing them with holograms. Two simulation sessions with emergency department clinicians were conducted using AR. The research team collected user feedback through simulations and interviews. Clinicians' feedback was systematically categorized and summarized according to various design elements. The integration of mock-up and AR simulations enabled the evaluation of design elements that were previously unattainable. Examples include simulating color-coded floor boundaries and adjusting door widths, which enhanced clinicians' immersion and involvement in design changes. Interviews and analyses of video recordings captured from the clinicians' perspectives supported the design evaluations during simulations. Augmented reality has great potential to be used widely in the evaluation of healthcare environment design. Augmented reality is an innovative approach that can benefit end-users in interacting with a mix of real spaces and virtual components. It also introduces new ways of data collection and analysis to architectural design evaluation methods.

Online monitoring and evaluation for conceptual design of product morphological structure driven by the retrospective analysis of cognitive behaviour

Monitoring and understanding designers’ design behaviour holds significant value for optimising the design paradigm and enhancing its quality and efficiency. This paper focuses on computer-aided conceptual design of product morphological structures, presenting a design monitoring and evaluation method driven by retrospective analysis of the association of designers’ cognitive behaviour. To begin with the monitoring perspective, the article analyzes the characteristics and collection methods of three types of design cognitive behaviour data. It also provides a behaviour element sequence transcription model, encompassing cognitive behaviour encoding, sketch behaviour encoding, and hierarchical encoding of design problems. Subsequently, a quantitative analysis index system is established with three dimensions: cognitive behaviour order, design state credibility, and thinking transition stability. By retrospectively analyzing the evolutionary relationships among fundamental design cognitive behavioural elements and referring to knowledge of design cognitive behavioural laws, designers’ cognitive preference type and state fluctuations can be distinguished. Finally, a hybrid fuzzy multi-attribute evaluation method is applied to filter various transcriptional combinations and calculate a comprehensive evaluation score. A real conceptual design experiment has preliminarily demonstrated the effectiveness of the introduced method.

A Queuing Model Based Rapid Evaluation Method for Automotive Control Design

This paper evaluates the ergonomics performance of automotive driving systems through a new computational model, aiming to enhance vehicle control design more cost-effectively than traditional experimental human factors research in the automotive field. Parameters such as spatial coordinates and control dimensions were measured for different driver interaction controls (e.g., hazard light switches, steering wheel buttons) across three typical passenger vehicles. These parameters were integrated into the QN-MHP-U to simulate driver operational behaviors and predict task performance. A computational method was introduced to assess the ergonomic scores of automotive control designs based on the modeling results. The QN-MHP-U provides a systematic and universally applicable solution for evaluating and comparing vehicle control designs within automotive driving systems. This allows automotive designers to assess and improve vehicle control designs from an ergonomic perspective more efficiently in terms of time and economic costs.

Evergreen or seasonal? Quantitative research on the color of urban scenic forests based on stress—attention electroencephalogram feedback

Urban scenic forests provide urban residents with various physical and mental health and wellbeing services. However, in the research on the color quantification and health services of scenic forests, it is still unclear how their color quantification characteristics feedback on the stress - attention of the adolescent group. In this study, visual color elements (green, red and yellow) of three landscape forests were used to generate 48 images of four groups of urban landscape forests according to color combinations and proportions. Virtual images were used to assess the stress indicators and attention indicators of participants before and after viewing. The results showed that the four groups of experimental groups showed varying degrees of α wave reduction and β/α ratio increase after viewing, G1 group showed an extremely significant increase in β wave after image stimulation, G1 and G3 group significantly decreased θ/β power, G4 group and G5 control group had no significant change. Among the 16 channels of absolute α wave and absolute β wave in the brain, the F3 and F4 channels corresponding to the frontal lobe of the G3 group showed the most prominent consistency of β wave in the frontal cortex during highly concentrated mental activities. Our study shows that positive EEG (Electroencephalogram) feedback of arousal and attention recovery can be obtained by using monochromatic or two-color changing color features in urban landscape forest. This study can provide references and methods for urban forest planning, design and visual evaluation.

Optimal Configuration of Physical Process Parameterization Scheme Combination for Simulating Meteorological Variables in Weather Research and Forecasting Model: Based on Orthogonal Experimental Design and Comprehensive Evaluation Method

The weather research and forecasting (WRF) model is frequently used to investigate the meteorological field around nuclear installations. The configuration of physical process parameterization schemes in the WRF model has a significant impact on the accuracy of the simulation results. Consequently, carrying out a pre-experiment to quickly obtain the optimal combination of parameterization schemes is essential before conducting meteorological parameter research. To obtain the optimal combination of physical process parameterization schemes from the planetary boundary layer (PBL), land surface (LSF), microphysical (MP), long-wave (LW), and short-wave (SW) radiation processes of the WRF model for simulating the near-surface meteorological variables near a nuclear power plant in Sanshan Town, Fuqing City, Fujian Province, China on 4 June 2019 were observed. Orthogonal experimental design (OED), a comprehensive evaluation method based on the CRiteria Import Through Intercriteria Correlation (CRITIC) weight analysis, and comprehensive balance method were employed for the first time to conduct the research. The sensitivity of meteorological variables to physical processes was first discussed. The findings revealed that the PBL scheme configuration had a profound impact on simulating wind fields. Furthermore, the LSF scheme configuration had a significant influence on simulating near-surface temperature and relative humidity, which was much greater than that of other physical processes. In addition, the choice of the radiation scheme had a significant impact on how the temperature was distributed close to the ground and how the wind field was simulated. Furthermore, the configuration of the MP scheme was found to exert a certain influence on the simulation of relative humidity; however, it demonstrated a weak influence on other meteorological variables. Secondly, The MYNN3 scheme for PBL process, the NoahMP scheme for LSF process, the WSM5 scheme for MP process, the RRTMG scheme for LW process, and the Dudhia scheme for SW process are found to be the comprehensive optimal physical process parameterization scheme combination for simulating meteorological variables in the research area selected in this study. As evident from the findings, the use of the OED method to obtain the combinations of the optimal physical process parameterization scheme could successfully reproduce the wind field, temperature, and relative humidity in the current study. Thus, this method appears to be highly reliable and effective for use in the WRF models to explore the optimal combinations of the physical process parameterization scheme, which could provide theoretical support to quickly analyzing accurate meteorological field data for longer periods and contribute to deeply investigating the migration and diffusion behavior of airborne pollutants in the atmosphere.

Blended Teaching Design of Hotel Customer Management based on Xuexi Tong

This paper explores the innovative application of a blended teaching mode for the core hotel management course, "Hotel Customer Management" (HCM), utilizing the Xuexi Tong learning platform. This study analyzes the platform's advantages for student learning and propose a comprehensive teaching design that has been implemented and evaluated using qualitative research methods. The results demonstrate that the Xuexi Tong-based blended teaching mode effectively stimulates student learning interest, fosters initiative, promotes deep learning, and cultivates practical abilities. This paper details the teaching design content, implementation process, and evaluation methods, offering valuable insights for promoting and applying blended teaching approaches in hotel management education.

Impact of Artificial Intelligence on Learning Management Systems: A Bibliometric Review

The field of artificial intelligence is drastically advancing. This study aims to provide an overview of the integration of artificial intelligence into learning management systems. This study followed a bibliometric review approach. Specifically, following the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) statement, 256 documents from the Scopus and Web of Science (WoS) databases over the period of 2004–2023 were identified and examined. Besides an analysis of the documents within the existing literature, emerging themes and topics were identified, and directions and recommendations for future research are provided. Based on the outcomes, the use of artificial intelligence within learning management systems offers adaptive and personalized learning experiences, promotes active learning, and supports self-regulated learning in face-to-face, hybrid, and online learning environments. Additionally, learning management systems enriched with artificial intelligence can improve students’ learning outcomes, engagement, and motivation. Their ability to increase accessibility and ensure equal access to education by supporting open educational resources was evident. However, the need to develop effective design approaches, evaluation methods, and methodologies to successfully integrate them within classrooms emerged as an issue to be solved. Finally, the need to further explore education stakeholders’ artificial intelligence literacy also arose.

EVALUATION OF NECK FATIGUE CAUSED BY WEARING HELMET IN MOTION: AN ELECTROMYOGRAPHY STUDY

The increased weight of multifunction and intelligent helmet systems can cause an exacerbation of the neck workload. Further, increased weight of the helmet can reduce the wearing comfort, and prolonged use may cause neck fatigue and even neck injury. This study evaluates the fatigue of neck muscles caused by wearing a helmet in motion using electromyography (EMG) measurement. Additionally, a comprehensive evaluation model for neck fatigue was established effectively. Twenty healthy subjects were selected to run for 10[Formula: see text]min continuously in each task by wearing two different helmets, respectively, during which the EMG signals of different neck muscles and subjective scores were recorded and analyzed. Two-way repeated measures analysis of variance (ANOVA) and Pearson correlation analysis were used to obtain indicators of neck fatigue, based on which the support vector machine (SVM) was used to construct a classification model of neck fatigue. By using integral EMG (IEMG) and root mean square (RMS) for assessing the neck injury in sternocleidomastoideus and trapezius muscles, it was observed that the mean power frequency (MPF) and median frequency (MF) in trapezius and splenius capitis could be used as effective evaluation indicators of neck fatigue. The EMG activity in trapezius was the highly sensitivity to fatigue when wearing helmets in motion. The classifier for distinguishing three different neck fatigue levels was 91.67% accurate. This study demonstrates the feasibility of an EMG-based method to evaluate the neck fatigue caused by wearing a helmet in motion, and also provides an evaluation method for the optimal design of helmets in the future.

Mechanism design optimization through CAD-based Bayesian optimization and quantified constraints

This study addresses the challenge of mechanism design optimization, particularly focusing on the energy efficiency and design space of reciprocating mechanisms. The research question centers on how to effectively utilize Computer-Aided Design (CAD) simulations alongside Bayesian optimization (BO) and a constrained design space to streamline the design optimization process, overcoming the limitations of traditional kinematic and dynamic analysis methods. The objective is to investigate and develop a novel optimization framework that integrates CAD-based simulations with a BO approach. To achieve this, the study employs a methodological approach. At first, the feasibility of a chosen mechanism design is evaluated through a sequence of CAD-motion simulations to quantify the (in)feasibility of this design. When this design appears to be feasible, a CAD-based design evaluation method is started, in which the objective value is extracted by a sequence of CAD-motion simulations. In this paper, we advocate the use of non-parametric Gaussian processes to build a surrogate model of the objective function and the feasible design space constrained by static and dynamic constraints. The main research results demonstrate that the proposed CAD-based Bayesian optimization framework can effectively identify optimal design parameters that minimize the root mean square (RMS) torque while adhering to specified static and dynamic constraints. This optimization approach significantly reduces the complexity associated with analytic methods, making it scalable to more complex mechanisms and implementable by machine builders. In conclusion, the study successfully develops a novel optimization framework that leverages CAD-based simulations and Bayesian optimization to streamline the design process of mechanisms. The results of an emergency ventilator case study with three design parameters show a reduction of the RMS torque with 71% after 255 CAD-based design evaluations. Moreover, the results demonstrate the effectiveness of incorporating constraints into the design optimization process and the usage of Bayesian optimization (BO), providing insights into the obtained optimum. This approach offers probabilistic insights into the expected improvement of the optimum, highlighting that the full optimization potential is utilized in a computationally efficient manner.

Augmented Reality User Interface: Analysing the Design Principles and Evaluation Methods of Augmented Reality (AR) User Interfaces to Enhance User Interaction and Experience

Augmented Reality User Interface: Analysing the Design Principles and Evaluation Methods of Augmented Reality (AR) User Interfaces to Enhance User Interaction and Experience

Intelligent Evaluation of Power Tool Design Based on Deep Learning

In order to address the issue of intelligent development in power tool design, this paper proposes an intelligent evaluation method for power tool design based on deep learning technology. The paper begins by summarizing the evaluation indicators for power tool design and constructing a hierarchical analysis model. It then utilizes FAHP to calculate the weight of each design indicator. Subsequently, pictures are collected and manually annotated to create a dataset for power tools. Finally, the dataset is refined and trained using the ResNet algorithm to develop an intelligent evaluation model for power tools, enabling the intelligent assessment of each evaluation indicator. By comparing the results of manual evaluation with those obtained through intelligent evaluation, it demonstrates the accuracy of the intelligent evaluation model based on ResNet algorithm and validates the effectiveness of this experimental approach.

The application of IGA in urban landscape design optimization

SummaryThe foundation of urban landscape design optimization is the precise evaluation of the effectiveness. To address the issues of strong subjectivity, low efficiency, and poor accuracy in urban landscape design evaluation methods, an intelligent evaluation method combining improved genetic algorithm and error backpropagation neural network is proposed. First, based on Maslow's demand theory and questionnaire survey results, it selects indicators to construct an evaluation index system for urban landscape design. Second, in response to the performance defects of the error backpropagation neural network model, the moth flame algorithm is used to optimize it. Then, in response to the defect that the optimization effect of the moth flame algorithm is not ideal enough, a multiple strategy including improved genetic algorithm is adopted to optimize it. Finally, an urban landscape design evaluation model is constructed based on improved error backpropagation neural network. The experimental results show that the fitting coefficient of the model is 0.9523, with a minimum deviation of less than 1%. The above results indicate that the proposed model can effectively improve the accuracy and efficiency of urban landscape design evaluation, providing data support for urban landscape design optimization. The research on the intelligent development of urban landscape design is of reference significance and has to some extent promoted the development of urban landscape design.

Optimal design of a combined Power-Heating-Oxygen system for plateau hotel buildings

The Qinghai–Tibet Plateau of China is a region of low atmospheric pressure and oxygen deficiency, with a high heating demand in the winter; therefore, plateau hotel buildings have a demand for comprehensive power-heating-oxygen loads. Solar energy resources are particularly abundant in plateau areas, where a combined multi-energy system based on solar energy can be designed to meet the demand of plateau hotel buildings for multiple loads. However, currently, there is a relative lack of methods for the optimal design and performance evaluation of combined power-heating-oxygen (CPHO) systems. Thus, this study proposes a CPHO system model for plateau hotels, and provides two operation strategies, i.e., power priority and oxygen priority. Taking the minimum total annual cost of the combined system as the optimization objective, an optimized CPHO system model for plateau hotels has been proposed, followed by a case study of a hotel in Qilian County, Qinghai Province. Results showed that: 1) Compared with the conventional combined power-heating (CCPH) system, the CPHO system saw reductions of 0.8% and 1.3% in its total annual cost under the operation strategies of power priority and oxygen priority, respectively. 2) The energy self-consumption (SC) rates of the CCPH system and CPHO system under the operation strategies of power priority and oxygen priority were 84.8%, 64.2%, and 89.8%, respectively; with power self-sufficiency (PSS) rates of 8.3%, 49.9%, and 29.5%, and oxygen self-sufficiency (OSS) rates of 0.0%, 3.2%, and 4.7%, respectively. 3) The total annual cost of the CPHO system was affected slightly by the cost of photovoltaics (PVs) and energy storage devices, and significantly by the price of oxygen. When the price of oxygen was 8 yuan per normal cubic meter(Nm3) or above, the CPHO system was economically efficient under the operation strategy of oxygen priority. When the price of oxygen was 10yuan/Nm3 or above, the system was economically efficient under both operation strategies.

Research on the Architectural Design and Performance Optimization of Large Scale Real-Time Chat Systems

With the rapid development of internet technology, large-scale real-time chat systems have become an essential tool for connecting users worldwide. These systems not only support the core functions of social communication but also serve as key platforms for business, education, and remote collaboration. However, the surge in user numbers and the explosive growth in message volume pose unprecedented technical challenges to real-time chat systems, including high concurrency processing, low latency communication, data consistency assurance, and system scalability. This study aims to explore and implement an efficient, stable, and scalable architecture for large-scale real-time chat systems and propose corresponding performance optimization strategies. The research employs literature review, system analysis, prototype design, and performance evaluation methods. It first analyzes the design limitations and performance bottlenecks of existing real-time chat systems. Based on this analysis, a microservices-based system design scheme is proposed, which enhances system performance and reliability through componentized services, message queues, load balancing, and caching mechanisms. In terms of performance optimization, this paper focuses on key technologies such as load balancing algorithms, asynchronous processing mechanisms of message queues, caching strategies, and data storage optimization. Experimental evaluations have confirmed the significant effects of the proposed scheme in handling high-concurrency requests, reducing system latency, and improving data throughput.

Application of Kansei engineering in the innovative design of traditional fashion elements

Kansei engineering can quickly establish the relationship between human emotion and product composition, and it is expected to be an important method for design evaluation. This paper investigates the application of Yungang Grottoes Bodhisattva necklaces to modern attire, specifically the cheongsam, with a focus on the Kansei Engineering-based design approach. The study introduces sensory evaluation to analyse the suitability of various types of Yungang Grottoes Bodhisattva necklaces in cheongsam designs and the sensual style of high-fit cheongsam designs. Two experiments were conducted, with Experiment 1 assessing the suitability of Yungang Grottoes Bodhisattva necklaces on different traditional cheongsam, and Experiment 2 examining the overall style of cheongsam designs when combined with Yungang Grottoes Bodhisattva necklace designs. Fuzzy logic was employed in Experiment 1 to evaluate the suitability of each necklace element, while Experiment 2 incorporated sensory evaluation to determine the sensual style of high-fit cheongsam designs, assessed through subjective ratings by 50 industry experts and 50 evaluators (women aged 18 to 35). The investigation utilized standard procedures for subjective evaluation experiments, resulting in the determination of the suitability of three mainstream cheongsam designs with 24 Yungang Grottoes Bodhisattva necklaces, as well as the identification of high-fit cheongsam sensual styles. The paper concludes by providing recommendations for the design of Yungang Grottoes Bodhisattva necklaces on the cheongsam, utilizing the relative weight values of cheongsam designs as guidance for future applications. This research contributes to understanding the integration of cultural artefacts in contemporary fashion, offering insights into design considerations and potential enhancements of the cheongsam through the incorporation of Yungang Grottoes Bodhisattva necklaces.

In silico degradation of fluoroquinolones by a microalgae-based constructed wetland system

Fluoroquinolone antibiotics (FQs) have been used worldwide due to their extended antimicrobial spectrum. However, the overuse of FQs leads to frequent detection in the environment and cannot be efficiently removed. Microalgae-based constructed wetland systems have been proven to be a relatively proper method to treat FQs, mainly by microalgae, plants, microorganisms, and sediments. To improve the removal efficiency of microalgae-constructed wetland, a systematic molecular design, screening, functional, and risk evaluation method was developed using three-dimensional quantitative structure–activity relationship models, molecular dynamics simulation, molecular docking, and TOPKAT approaches. Five designed ciprofloxacin alternatives with improved bactericidal effects and lower human health risks were found to be more easily degraded by microalgae (16.11–167.88 %), plants (6.72–58.86 %), microorganisms (9.10–15.02 %), and sediments (435.83 %–1763.51 %) compared with ciprofloxacin. According to the mechanism analysis, the removal effect of the FQs can be affected via changes in the number, bond energy, and molecular descriptors of favorable and unfavorable amino acids. To the best of our knowledge, this is the first comprehensive study of improving the microalgae, plants, microorganisms, and sediment removal efficiency of FQs in constructed wetlands, which provides theoretical support for the treatment of FQ pollution.

Optimization of inclined coal seam tunnel section angle and anchor angle based on response surface method

The mining of inclined coal seams is often accompanied by problems such as difficult to control deformation of the tunnel roof and failure of anchor bolts. Taking the transportation channel of Jinping Coal Industry 1071-1 in Shanxi Xiangkuang Mine as the background, FLAC3D numerical simulation software was used, and the method of response surface experimental design and data analysis was used to systematically study the effects of the anchor installation angle and the roof inclination angle of the tunnel section on different inclination angles. Influence of the surrounding rock stability of coal seam roadways. On this basis, a multi-index tunnel support design evaluation method based on the response surface method was proposed, and the actual support plan was optimized and industrial tests were carried out based on the actual on-site support plan. The research results show that: in terms of inclined coal seam support, the degree of influence on the tunnel stability is in the following order: anchor installation angle > tunnel section roof inclination angle > coal seam inclination angle; the optimized support design obtained through the proposed technology The method has good application effect and can improve the stability of the roadway during the mining of the working face. It also proves the effectiveness of this technology and provides new ideas for the design of anchor support of inclined coal seam roadways and the optimization of roadway sections.

Shear strength of prestressed concrete beams with short shear span: Full‐scale experiments and evaluation of design methods

AbstractPrestressed concrete (PC) is increasingly used in civil engineering construction. Notably, research on shear resistance in PC beams with short shear span remains relatively limited, necessitating further comprehensive exploration. In the study, tests were conducted on bonded post‐tensioned PC T‐beams with short shear span (a/h = 1.0), subjecting them to monotonic loading destructive tests. These beams measured 24.9 m in length, 1.605 m in height, and had a top flange width of 2.0 m. They featured a uniform cross‐section with a 0.22 m web thickness. Given the size of the full‐scale test beams and space constraints for loading, an innovative loading scheme was devised to minimize the counterweight. Test results demonstrate the safety and feasibility of the loading scheme. The tests were conducted five times and the main test variables were the draped tendons and the quantity of horizontal web reinforcement. The tests revealed that horizontal web reinforcement significantly influenced crack propagation but had a minimal effect on shear strength. For the parameter values taken for the test beams, the prestressing level has less effect on the shear strength of the beam. Simultaneously, an investigation was conducted involving a total of 119 PC beams. This investigation aimed to evaluate the degree of conservatism and accuracy in shear design code provisions and shear strength equations derived from various standards, including the strut‐and‐tie model (STM) of ACI, AASHTO, and Tan, as well as the critical crack model of Yuan and the truss model of Laskar. Comparative analysis indicates that, the design method provided by Yuan exhibit relatively superior predictive capabilities.

Evaluation of electric car styling based on analytic hierarchy process and Kansei engineering: A study on mainstream Chinese electric car brands

To evaluate the fuzzy and uncertain factors brought by human's emotional sensibilities during the design of new energy vehicle models, a scientific design evaluation method was adopted. This study combines the Analytic Hierarchy Process (AHP) and Kansei Engineering to assess the design of new energy vehicle models. It uses both objective criteria and subjective user perceptions. First, it quantified the design imagery vocabulary through Kansei Engineering and identified the target imagery vocabulary. Secondly, the AHP method was used to establish a relationship between design features and imagery vocabulary. Thrid, the study created an evaluation index system for design imagery, and adopted the fuzzy comprehensive evaluation matrix to rank the representative vehicles and brands in the Chinese new energy vehicle market. Based on the weight analysis results, the vehicle functionality (whether it is safe and reliable), the elegance of design, and the intricacy of vehicle structure were identified as the top three aspects that affect the impression of new energy vehicles. Therefore, we need to focus on these aspects during the design of new energy vehicles. Additionally, by integrating objective evaluation and emotional analysis results, we assessed the design for each new energy vehicle brand. The results of this study are important for developing the new energy vehicle market.