Radar Chart Research Articles

Preparation and Performance of Bitumen Modified by Melt-Blown Fabric of Waste Mask Based on Grey Relational and Radar Chart Analysis.

To effectively utilize waste mask materials in road engineering and minimize resource waste, the melt-blown fabric (MBF) of waste masks was utilized to modify the virgin bitumen. The preparation process of MBF-modified bitumen was investigated, and the physical and rheological properties of bitumen were measured. Subsequently, the blending mechanism during preparation and the dispersion morphology of the modifier were explored. Finally, the pavement performance of the mixture was investigated, and a radar chart analysis was performed to quantitatively assess the effects of MBF modification. Results suggested that the recommended preparation process of shear time, shear rate, and shear temperature was 170 °C, 4000 r/min, and 15 min, respectively. MBF enhanced the high-temperature stability of the binder and weakened the temperature susceptibility. The modification was primarily a physical process. No network structure and agglomeration formed in the bitumen after modification. The addition of MBF significantly improved the resistance of the asphalt mixture to a high-temperature deformation and water damage but harmed its low-temperature crack resistance. The comprehensive assessment results of 0% (f1), 1% (f2), 3% (f3), and 5% (f4) MBF to improve the properties of the mixture were in the following order: f3>f4>f2>f1, where the impact of 3% MBF was the most significant, followed by 5% and 1% MBF.

A multiple-objective capacity allocation optimisation method for cogeneration integrated energy systems considering life cycle carbon emission

ABSTRACT With the increasing penetration of renewable sources, the cogeneration integrated energy system (CIES) is much more efficient and flexible to achieve various types of energy supply for remote loads. Due to uncertainties in both sources and loads, the CIES should be carefully planned and optimised to keep it working at the suitable operation condition. Therefore, this paper proposes a multi-objective capacity allocation optimisation method for the islanded CIES, which is composed of renewable energy generation unit, electric-thermal conversion unit, electric storage, thermal storage and various loads. Firstly, three optimisation objectives are selected as typical indexes, including economic cost, solar energy utilisation, and life cycle carbon emission. An improved radar chart evaluation (RCE) solution is subsequently utilised for calculating a fitness function and building the multi-objective optimisation model. Besides, several compulsory constraints are supplemented to ensure the overall CIES performance satisfy energy supply requirement. As a mature and widely accepted algorithm, a genetic algorithm is chosen as an example to obtain the optimal capacity allocation scheme. Case study of an islanded CIES is provided on the basis of real data from the remote region of northwestern China, which successfully verifies the effectiveness of the proposed optimal capacity allocation method.

Ergonomic Workspace Design to Reduce the Risk of Musculoskeletal Disorders

Office activities were closely tied to document handling and computer interaction. Based on initial identification with the Nordic Body Map, MSDs (Musculoskeletal Disorders) complaints were identified in the shoulders, wrists, waist, buttocks, and back. This study aimed to offer recommendations for enhancing office workstations to minimize the risk of MSDs. The methods used are ROSA to identify employee work postures, product design to provide proposed work facilities, 5S for document organization, and a Radar Chart for evaluation. Initial identification shows the problems that exist in work facilities, workspace layout, and work environment factors. The initial identification of the workspace with Radar Chart also showed a poor score on 5 aspects of Seiri, Seiton, Seiso, Seiketsu, and Shitsuke with an average of 41.75. The proposed intervention is the improvement of ergonomic tables and chairs, structuring documents by applying 5S aspects, and improving the layout of the workspace. The proposed improvements were then evaluated again using the Office 5S Audit Checklist and Radar Chart so that after the ergonomics intervention, the Radar Chart value became 90.75 (excellent) and the 5S aspects (Seiri, Seiton, Seiso, Seiketsu, and Shitsuke) increased. The results of this improvement can be expected to overcome the risk of MSDS problems in the lower neck, buttocks, back, and waist and the resulting ergonomic, organized, and efficient workstations.

Intervention on Mathematics Self-Efficacy: Solution-Focused Brief Therapy.

Research has demonstrated a strong correlation between mathematics self-efficacy and math performance. Middle school children are increasingly receiving solution-focused brief therapy (SFBT), which is a type of psychotherapy. The study intends to use SFBT intervention to improve mathematics self-efficacy of students and to determine whether SFBT intervention was effective. To examine whether Rasch model can be used to evaluate students' mathematics self-efficacy. This study intends to use Radar chart, Rasch model, Line chart to measure the variations of mathematics self-efficacy of three 8th graders (n=3) during SFBT intervention. Radar chart and Rasch model demonstrated a general increment in the mathematics self-efficacy of two pupils, while another one decreased. Additionally, three students showed a decline in their mathematics self-efficacy on particular mathematical problems using a line chart. Overall, students with varied degrees of self-efficacy in math benefited from SFBT interventions, which partially supports the usefulness of SFBT as a tool for assessing students' mathematics self-efficacy. It supported that Rasch model can reflected the changes in students' mathematics self-efficacy. This study provides guidance for measuring the improvement of students' academic self-efficacy through SFBT intervention using Rasch model.

Scenario simulation and synergistic effect analysis of CO2 and atmospheric pollutant emission reduction in urban transport sector: A case study of Chengdu, China

Realizing coordinated control of CO2 and atmospheric pollutants in comprehensive transportation in large cities is an important way to promote sustainable urban development. Based on the LEAP framework, this study established a transport CO2 and atmospheric pollutant emission analysis model for Chengdu from 2021 to 2040, set up three main scenarios for the study of carbon peaking trend and 12 sub-scenarios for the study of the synergistic effect of various emission reduction measures. In addition, the synergistic effects were analyzed by radar charts, grading charts of synergistic effects and the synergetic equivalence index. The results show that under the Green Scenario (GS) and the Strengthen Green Scenario (SGS), the CO2 emissions from comprehensive transportation in Chengdu will peak at 26.774 × 106 t and 23.507 × 106 t in 2032 and 2029, respectively. The emissions of other atmospheric pollutants show a general downward trend. Under SGS, The measures that play the greatest role in reducing CO2, CO, VOCs, and NOx emissions by 2040 are NEV (New energy conversion of vehicles), Among them, the CO2 emission reduction rate relative to BS scenario is 20.7%. While the measures that play the greatest role in reducing PM and SO2 emissions are IES (Improvement of emission standards) and SRT (Strengthen railway transportation), respectively. Compared with other measures, the synergistic effect of SRT is the most highest. The emission reduction effect of NEV is most significant, with a synergistic effect level above level II. Under the joint regulation of multiple measures by GS and SGS, the synergistic equivalence index based on air quality standards has been effectively controlled, showing a downward trend. Overall, Chengdu faces challenges due to a large number of motor vehicles and air passenger throughput. Therefore, vigorously developing hydrogen vehicles and electric vehicles, strengthening railway construction in Chengdu, transferring the pressure of civil aviation and road transportation to railway, can make significant contributions to the pollution reduction and carbon reduction of Chengdu's transportation sector.

Customized and Optimized Treatment of Extended-Spectrum-Beta-Lactamase Bacteria for Individual Patients

This paper discusses the optimization of customized intravenous-drip therapy regimens for individual patients infected with antibiotic-resistant bacteria, namely Extended-Spectrum-Beta-Lactamase (ESBL) bacteria. By utilizing Ordinary Differential Equations (ODE) to model the system’s dynamics, evaluated the efficiencies of the four most typical types of pulse functions, namely Dirac delta, sine, trapezoid, and normal distribution functions, as well as the time required for each treatment to suppress the pathogen population. The results revealed that a trapezoid pulse function for intravenous delivery of antibiotics is most favorable. Subsequently, infection severity was randomized by altering the bacterial and Beta-Lactamase population. The efficiency of each randomized regimen was evaluated using a predetermined score matrix that assessed the dosing length, dosing interval, maximum rate of antibiotic infusion, net consumption of antibiotics, and the total number of required treatments. Radar charts and box plot models were employed to present the findings. It was discovered that for more severely infected patients with a higher initial population and growth rate, it is important to decrease the time interval between subsequent doses and increase the time of maximum infusion rate. Conversely, for mild infections, the time interval between doses should be increased, and the time of maximum infusion rate should be decreased. It should be noted that maximizing the infusion rate does not enhance treatment efficiency. Furthermore, in comparison to the initial infected bacteria population size, the growth rate, and Bla production rate play more important roles in impacting treatment efficacy.

Evaluation Method of Teaching Quality of Foreign Language Teachers in Colleges and Universities Based on Decision Tree Algorithm

Abstract Teaching evaluation is an important part of the teaching process in colleges and universities and plays a very important role in the development of higher education and the improvement of education quality. Applying a decision tree algorithm to teaching evaluation can uncover the hidden intrinsic connection between teacher information and course quality evaluation results. This study combines the radar graph with the decision tree C4.5 algorithm to construct a foreign language teaching quality evaluation model, which explores the correlation between teacher information and radar graph attributes on teaching quality evaluation grades on the one hand and evaluates the predictive effect of the model on the other hand. The data mined by the radar chart-C4.5 evaluation model show that if the center of gravity of the radar chart is in the first quadrant, then the evaluation grade passes and has the highest support, which is 53.33%. If the radargram area is large, then the evaluation grade good has the highest confidence level of 77.27%. The evaluation result of the model is that the number of error samples of the prediction grade and the expert evaluation grade are 3 excellent, 5 good, 1 average, 4 qualified, and 1 poor, which proves that the performance of the radar map-C4.5 evaluation model is better.

Entropy-Based Thunderstorm Imaging System With Real-Time Prediction and Early Warning

A combination of the sample entropy and the artificial intelligence (AI) would hopefully bring progress to the smart thunderstorm detection. In this paper, we establish an entropy-based thunderstorm point charge imaging system with the data clustering, wherein data are ultra-reliable and have low-latency three-dimensional atmospheric electric field (3DAEF) values. In particular, a high resolution 3DAEF sensor with the single-axis rotary vane is developed to measure the time sequence signal of the 3DAEF. The signal is first denoised, and then decomposed into multiple groups of branch data with the same number of samples. In order to break through the limitations of existing clustering rules, we propose a 3DAEF signal reconstruction method based on entropy intervals. By reconstructing the branch data, multiple time-scale data are formed. Finally, the curve fitting of the data is performed to realize the imaging after clustering the data. Experimental results suggest that the imaging error after the clustering is reduced by about 2.33%. Comparisons with radar charts show that the proposed system can effectively image the point charge moving paths.

Research on the Teaching Reform of Art and Design Courses in Colleges and Universities Driven by Artificial Intelligence

Abstract This paper focuses on analyzing the critical technologies of artificial intelligence technology in the creation and display of art and design teaching in colleges and universities, respectively, using image processing technology, image geometric transformation, and image special effects processing to realize the basic image design of art design, and using head-eye synergistic eye-movement multi-channel interaction and gesture interaction to form an immersive interactive art and design display device. Combined with the radar chart of the acceptance of AI technology in the course teaching, the influencing factors of the three dimensions of cognition, interest and Practice are explored. The OBE concept is introduced to propose a teaching reform program for art and design courses under AI technology. Practical application of the teaching program can improve students’ visual literacy in art and design, and its numerical difference is 0.3254 at the most. Thus, the teaching reform program of art and design courses in colleges and universities based on the OBE concept proposed in this paper is feasible to a certain extent.

Facilitating the learning and adaptation process of regional initiatives that transform towards health and wellbeing systems.

Introduction: Health-systems in western countries are under pressure due to increasing costs, changing health care demands, and a growing shortage of staff. Therefore, regional initiatives are searching for ways to integrate and reorganize services across domains. This is a complex process and requires an incremental approach based on reflection and adaptation. However, regional initiatives are still searching how to construct these processes. This study aimed to gain more understanding of how the reflection and adaptation process in regional initiatives could be facilitated.
 Methods and analysis: This study included an action research within a Dutch regional initiative, including the program managers, involved municipalities, province, health care insurer and the public health services. The partners reflected on transformation themes, identified in previous evaluation studies, by scoring them in questionnaires and discussing them in interviews. Finally, two reflection meetings were facilitated with representation of all partners, respectively on management and board level. The program manager was interviewed about the experiences with this action research. Notes of this interview and observations of the reflection sessions were analyzed inductively. To broaden the experiences within this one initiative, the experiences with the reflection process were reflected upon in semi-structured interviews with program managers from other regional initiatives (n = 11). The semi-structured interviews were coded and clustered inductively.
 Results: Based on the scoring in questionnaires and interviews a radar chart was shown in the reflection meetings. This highlighted that especially two themes (accountability and citizen participation) would need adaptation. Partners especially recognized the problems regarding accountability and agreed that further elaboration was needed. One of the aims of the reflection process was to create a collective feeling of ownership. Results show that external facilitation of the reflection process, which was objective and knowledge-based, helped to enhance the collective conversation. Reflecting with the program managers of the other initiatives learned that not all initiatives invested in a regional reflection and adaptation process. Lack of this investment was related to partners not prioritizing this process. Some program managers expected the knowledge-based reflection to be helpful in creating a common ground among the partners. The use of scoring, like in the questionnaires, or having actionable options after scoring the themes was expected to be helpful to be able to act upon the reflection.
 Lessons learned and next steps: This study described the experiences with facilitating reflection and adaptation processes of regional initiatives. It showed that knowledge-based reflection by an external facilitator was valued to enhance the collective conversation and common ground about transformation. Further research is needed to learn how this common ground could eventually result in adaptation of the initiatives and thus aid their transformation. This research identified the importance of creating a collective process amongst partners for learning and adaptation, though found that not all initiatives invested in this process due to other priorities. More awareness among partners of the initiatives is needed about the importance of this process for transformation and their role in this collective process.
 

Dual characterization method of temperature uniformity and fluctuation for refrigerator: Experiment, methodology, and improvement

Temperature uniformity and temperature fluctuation are two important parameters of refrigerator and have significant effects on fresh-keeping and cold-storage technology. The influencing factors of temperature distribution attract more attention in refrigerator factory. However, the definitions of temperature uniformity and temperature fluctuation are still ambiguous, and present characterization methods cannot accurately describe the temperature field of refrigerator. This paper proposed a novel dual characterization method to reveal the temperature uniformity and fluctuation (TUF) and presented a new arrangement strategy of temperature measuring elements in refrigerator. Results show the proposed method can simultaneously and visibly characterize the TUF behavior. The slope and area of curves in temperature radar chart reveal the TUF distribution clearly. The first layer of refrigerator shows a greater temperature fluctuation, especially when the compressor is working. Refrigerators with different volume have different TUF phenomena. Adding a cold storage module on the top of refrigerator can notably improve TUF feature and make the internal temperature closer to target temperature. The mechanism of TUF change was discussed from heat transfer and cascaded energy utilization. The proposed dual characterization method can reveal temperature distribution with space and time simultaneously and help improve the temperature field of cold-heat preservation to save energy.

Greenness, whiteness, and blueness assessment with spider chart solvents evaluation of HPTLC-densitometric method for quantifying a triple combination anti-Helicobacter pylori therapy

Tackling environmental, economic, and practical issues necessitate analytical methods aligned with green and white chemistry principles. This study quantified a challenging combination of three anti-Helicobacter pylori drugs: omeprazole (OMZ), tinidazole (TNZ), and clarithromycin (CLR) using a novel high-performance thin-layer chromatographic approach. The eco-friendly mobile phase comprised a mixture of ethyl acetate and ethanol (6.5:3.5, v/v), with densitometric detection at 290 nm, yielding compact spots for OMZ (Rf 0.27), TNZ (Rf 0.63), and CLR (Rf 0.73). The method demonstrated excellent linearity (r2 > 0.999) over ranges of 0.5–20, 1–50, and 1–25 μg spot−1 for OMZ, TNZ, and CLR, respectively. Method validation showed good precision (<2 %), accuracy (101.94, 100.65, 101.06 %), and the limit of detections (0.161, 0.269, and 0.283 μg spot-1), for OMZ, TNZ, and CLR, respectively. To ensure sustainability, hazardous solvents were replaced with greener alternatives selected using the Green Solvents Selecting Tool and assessed via greenness index spider charts. The greenness evaluation of the developed method achieved a greener National Environmental Method Index (NEMI), and Complementary Green Analytical Procedure Index (ComplexGAPI) quadrants with higher Analytical Greenness Metric (AGREE) (0.81) and lower carbon footprint (0.037) revealing the method's favorable environmental profile. We further applied the concepts of 'blueness' and 'whiteness' assessment using the recently introduced Blue Applicability Grade Index (BAGI) and Red-Green-Blue 12 (RGB 12) algorithms. The high BAGI score (90) indicated excellent applicability, while the RGB12 score (88.9) confirmed cost-effectiveness and sustainability. This novel HPTLC approach offers a rapid, green-and-white alternative to conventional techniques for pharmaceutical analysis.

How to Use Costs in Value-Based Healthcare: Learning from Real-life Examples

BackgroundHealthcare organizations measure costs for business operations but do not routinely incorporate costs in decision-making on the value of care.AimProvide guidance on how to use costs in value-based healthcare (VBHC) delivery at different levels of the healthcare system.Setting and ParticipantsIntegrated practice units (IPUs) for diabetes mellitus (DM) and for acute myocardial infarction (AMI) at the Leiden University Medical Center and a collaboration of seven breast cancer IPUs of the Santeon group, all in the Netherlands.Program Description and EvaluationVBHC aims to optimize care delivery to the patient by understanding how costs relate to outcomes. At the level of shared decision-making between patient and clinician, yearly check-up consultations for DM type I were analyzed for patient-relevant costs. In benchmarking among providers, quantities of cost drivers for breast cancer care were assessed in scorecards. In continuous learning, cost-effectiveness analysis was compared with radar chart analysis to assess the value of telemonitoring in outpatient follow-up.DiscussionCosts vary among providers in healthcare, but also between provider and patient. The joint analysis of outcomes and costs using appropriate methods helps identify and optimize the aspects of care that drive desired outcomes and value.

Extent of integration of nutrition assessment counselling and support interventions in the health system and respective drivers: A case of Tororo district, Uganda.

Uganda embraced Nutrition Assessment Counselling and Support (NACS) since 2009 as a health system strengthening approach to improve health and nutrition outcomes. However, scant evidence exists on NACS integration and drivers. This study therefore assessed the extent of NACS integration in the health system and identified key drivers and barriers. A mixed method design was employed. In a facilitated panel discussions at each of the 17 health facilities, 4-5 health staff participated, responding to a semi-structured questionnaire. Integration was assessed on a 5-point scoring scale of 1 for not done nor integrated, 2-4 for partial and 5 for fully integration. Data was captured, analysed in microsoft excel and presented using as bar and spider charts. Integration drivers were identified deductively from key informant and in-depth interviews using Atlas.ti 9 and thematic analysis. The NACS integration across the health facility level was partial at a score of 2.9 indicating a weak integration into the health system. Integration across the health system building blocks was partial at; service delivery (3.8), health work force (3.7), health information (3.3), community support system (3.0), governance and leadership (3.0) signifying that NACS activities are provided by Ministry of Health but sub-optimal due to weak capacities. Health financing (2.2) and Health supplies (1.5) were the least integrated due to partner dependence. Under service delivery, deworming (5) was fully integrated and provided by Ministry of Health. The key drivers for integration were; good leadership, financing, competent staff, quality improvement approaches, nutrition talks, community dialogues, nutrition logistics and supplies. The NACS integration in the health system was generally low and lacked adequate support. Governance, financing and community follow-up under service delivery require more government investment for enhanced integration.

Impact of emerging sustainable aircraft technologies on the existing operating ecosystem

Emerging sustainable aircraft technologies—such as sustainable aviation fuel, electric and hydrogen propulsion—are expected to play a major role in the decarbonization of the aviation sector. Nevertheless, at present, the exact impact that their deployment will have on the existing operating ecosystem is not yet clear. To shed some light on this area, this paper adopts an exploratory research approach based on the collection of impact assessments through semi-structured interviews with domain experts. In particular, we involve 22 individuals affiliated with the most important stakeholders in the European and American aviation industries, including airlines, airports, aircraft and engine manufacturers, fuel producers, government agencies, universities and research centers, and aviation industry experts. Our results, that are presented in the form of spider charts and tables, provide an exhaustive and comprehensive picture of all the impacts that the examined technologies are expected to have on airline operations, airport operations, and airside airport infrastructure. What emerges is that SAF, even if used in high percentages, is anticipated to have a fairly marginal effect. In contrast, electric and hydrogen aircraft propulsion are foreseen to be much more disruptive, having a similar medium-to-high impact on many operations and parts of the airport infrastructure. In light of this finding, we propose the development of multi-technology airport infrastructural assets as a solution not only for the possible onset of lock-in effects but also for the chicken and egg dilemma currently affecting the sector.

TCGAplot: an R package for integrative pan-cancer analysis and visualization of TCGA multi-omics data

BackgroundPan-cancer analysis examines both the commonalities and heterogeneity among genomic and cellular alterations across numerous types of tumors. Pan-cancer analysis of gene expression, tumor mutational burden (TMB), microsatellite instability (MSI), and tumor immune microenvironment (TIME), and methylation becomes available based on the multi-omics data from The Cancer Genome Atlas Program (TCGA). Some online tools provide analysis of gene and protein expression, mutation, methylation, and survival for TCGA data. However, these online tools were either Uni-functional or were not able to perform analysis of user-defined functions. Therefore, we created the TCGAplot R package to facilitate perform pan-cancer analysis and visualization of the built-in multi-omic TCGA data.ResultsTCGAplot provides several functions to perform pan-cancer paired/unpaired differential gene expression analysis, pan-cancer correlation analysis between gene expression and TMB, MSI, TIME, and promoter methylation. Functions for visualization include paired/unpaired boxplot, survival plot, ROC curve, heatmap, scatter, radar chart, and forest plot. Moreover, gene set based pan-cancer and tumor specific analyses were also available. Finally, all these built-in multi-omic data could be extracted for implementation for user-defined functions, making the pan-cancer analysis much more convenient.\\ConclusionsWe developed an R-package for integrative pan-cancer analysis and visualization of TCGA multi-omics data. The source code and pre-built package are available at GitHub (https://github.com/tjhwangxiong/TCGAplot).

Sustainability performance of rural municipalities in Germany

BackgroundSustainable rural development entails efforts to enhance the well-being of rural communities while safeguarding natural resources for future generations. The thorough examination of sustainable rural development is still scarce but nevertheless crucial, as it enables to reveal the various challenges and remaining potentials in rural areas, to identify key stakeholders and their respective roles in promoting sustainable rural development, and to determine the best practices for attaining set goals along the various sustainability dimensions considered. Germany has implemented a range of policies, initiatives, and programs to foster sustainable development, extending its efforts to also encompass rural areas. This study assesses the sustainability performance of rural municipalities in Germany, proposing a novel and comprehensive sustainability benchmarking system. For this purpose, the performance of selected rural municipalities along the ecological, social, economic, and technological dimensions is examined.ResultsBased on the systematic implementation of methodological stages, a rigorous literature review process, a systematic indicator selection, and stringent filtering criteria, the selected indicators of our study cover environmental, energy, quality of life, economic, and technological aspects. These indicators enable to efficiently and effectively measure, compare, and evaluate the sustainability performance of rural municipalities. After normalization, weighting, and aggregation of the considered indicators, the performance is visualized in radar charts. Radar charts are handy for comparing a larger number of variables and displaying them in compact and comprehensible form in a single chart. Finally, the overall relative sustainability performance of the selected rural municipalities in Germany is compared based on an aggregated single score. The adopted methodology of aggregating indicators enables us to assess the sustainability performance of municipalities as well as to highlight variations among them.ConclusionMost databases and sustainable development reports are updated only every couple of years and often do not report the performance of small rural municipalities but only larger (more urban) ones. By conducting a detailed analysis of these specific cases, we can identify key challenges and opportunities unique to rural communities and develop targeted strategies for a more sustainable development. Adding digitalization as a technological value indicator makes our approach more comprehensive than comparable others, and accounts for the important new sustainability dimension of societal transition. This study contributes to the existing literature by proposing a novel sustainability benchmarking system specifically tailored for rural areas. From a practical standpoint, the developed sustainability benchmarking system offers a practical tool for rural municipalities to assess and monitor their sustainability performance and to reflect on variations among them. The identified dimensions and indicators can guide the development of targeted strategies and interventions aimed at enhancing sustainability in rural communities. Finally, policymakers can utilize the benchmarking results to design policies, (incentive) programs, and initiatives that address the specific sustainability challenges faced by rural municipalities and account for limitations in the local potentials.

Development of a readiness model for industry 4.0 using Analytical Hierarchy process and fuzzy inference system: Bangladesh perspective

The rapid acceleration of innovation and the marvels of science and technology have introduced mankind to a new era known as the Fourth Industrial Revolution or Industry 4.0. As a developing country, Bangladesh should not lag behind in the concept of the domain known as Industry 4.0. A substantial number of industries across Bangladesh are coming forward to take on the challenges associated with this novel concept. It is, however, reported that many of them are now at the embryonic stage and only taking pilot initiatives. Before entering the domain of Industry 4.0, an industry must check its readiness and maturity to access the field, and that's where it comes to the importance of the readiness model. The main objective of this research is to propose a new readiness model based on the perspective of Bangladesh and developing countries like Bangladesh. Analytical Hierarchy Process and Fuzzy Inference System has been used for developing the model. There are four readiness levels in the proposed model that dictate the readiness of any particular industry. Through systematic literature review and expert opinion, 6 dimensions and their associated field have been identified for the determination of readiness level. In the later part of the research, a case study on one of the companies in the garments industry has been accomplished, and a radar chart is presented in order to illustrate the readiness of that garments industry. The results from the case study indicate that the ABC garments industry is in the Survival stage and several recommendations are then provided to cope better in that situation.

Research on T-shirt-style design based on Kansei image using back-propagation neural networks

Abstract Users’ Kansei image preferences have become one of the most important factors influencing purchase decisions. However, defining Kansei image can be complex. To address this issue, researchers have widely applied back-propagation neural networks due to their capacity to handle extensive data, adaptively adjust weights and biases, conduct multi-class classification and regression predictions, and offer interpretability analysis, among other features. In this study, a clothing-style design model based on users’ Kansei image cognition is proposed, using collarless T-shirts as an example. Furthermore, the attributes of T-shirt patterns are quantified using parametric graphics principles, and a semantic scale system for emotions is established through user research. The quantified sample data and corresponding semantic scale scores are then used as inputs for training a back-propagation neural network algorithm. Consequently, a design model grounded in users’ Kansei image cognition is developed, resulting in five optimal clothing design forms across various Kansei image categories. Additionally, the styles are showcased through the Style 3D platform, and the design evaluation is presented using radar charts. The results demonstrate that the five female T-shirt designs generated by the model align with users’ style preferences based on Kansei image.

The application of the Resilience Assessment Grid in outpatient clinics: A validation study

The Resilience Assessment Grid (RAG) has gained increasing traction in healthcare discourse for its effectiveness in understanding and assessing the potential resilient performance of healthcare organisations. RAG is intended to be tailored for the specific organisation. However, developing a context specific RAG questionnaire can be time-consuming, limiting its widespread implementation. The current study aimed to investigate whether an existing Danish RAG questionnaire for outpatient clinics could be successfully content validated and applied in another outpatient clinic context.A modified Delphi method was used to content validate the Danish RAG questionnaire in the Australian outpatient clinic setting, using interviews and expert panel reviews. The 29-item English version of the RAG questionnaire was administered in 2023 to nine managers and five healthcare professionals responding on a five-point Likert scale, who work across 34 hospital outpatient clinics at Macquarie University (MQ) Health Clinics. The questionnaire was also employed during managerial and departmental meetings in a collaborative learning format. Descriptive statistics were used to analyse the data, which was then presented using radar charts to facilitate the interpretation of the resilient profiles of MQ Health Clinics.The translation and validation of the Danish RAG questionnaire was successful. The English language RAG questionnaire was perceived as useful by managers to assess their clinics’ resilient strengths and weaknesses and identify areas for improvement within their clinic.While the RAG methodology highlights the importance of context-specificity, this study’s findings suggest that the content validated RAG questionnaire has the potential for application in other outpatient settings with minimal adaptation.