Assessing the health of wetland using the PSR approach with reference to the Renuka Ramsar Site, India.

Wetlands are important ecosystems, and few of them, owing to unique characteristics, have been designated the status of Ramsar sites under the convention of wetlands. Despite the status, few of these wetlands are under threat owing to their social importance. Renuka wetland is one such important Ramsar site in India, which is culturally an embodiment of the Goddess Renuka ji. An international fair is held every year at the lake which attracts thousands of pilgrims and tourists. This event is one of the major contributors to anthropogenic risk; other pressures are siltation, pollution, land use activities, and invasive species. Under such a scenario, it becomes important to assess the health of wetlands to take timely decisions about their management. This study evaluates the health of Renuka wetland, using the Pressure State and Response (PSR) model. Relevant data related to the wetland and its catchment from a wide spectrum of sources, namely, field, laboratory, and remote sensing were combined to assess the health of the wetland. Ten indicators were identified, and Analytic Hierarchy Process (AHP) was used to assign weights to the indicators. The wetland health index of Renuka wetland is 0.35, indicating that the lake is in poor condition exhibiting degraded functioning, high external pressure, low vigor, poor resilience, and stability. The study also revealed that the water quality deteriorates post-fair. Thus, the wetland needs attention in terms of management so that the health of the lake improves and is sustained in the future. The study contributes to Sustainable Development Goal 6.6 which focuses on protecting and restoring water-related ecosystems and aims at healthier ecosystems.

Estimating weight for multidimensional health poverty using Delphi method and analytic hierarchy process: a case of China.

BACKGROUND: Traditionally, poverty assessment has relied on a single income criterion, which is inadequate in contexts where absolute poverty has been mitigated. This study developed a weighting scheme for the Multidimensional Health Poverty Index (MHPI) based on sustainable livelihood framework (SLF), aimed at enhancing the accuracy of poverty identification in China. METHODS: A two-round Delphi process was used to determine the indicators of the index system. The weight of each indicator was calculated using the analytic hierarchy process (AHP) method. The multidimensional poverty index incorporates SLF's five dimensions: financial, natural, physical, social, and human capital. RESULTS: The initial 46 indicators formed an indicator pool for the Delphi questionnaire. Based on the final consensus of the expert panel, the Delphi consultation resulted in an index system comprising six first-level and 23 second-level indicators. The weight values of the first-level indicators (economic security, health status, education, social capital, healthcare utilisation, and living conditions) were 0.2715, 0.2593, 0.0855, 0.0657, 0.1812, and 0.1363, respectively. CONCLUSION: This study established a scientific and effective index to evaluate generate weight for estimating multidimensional health poverty in China. Economic security, health status, and healthcare utilisation are the most crucial aspects of multidimensional health poverty. Moreover, the results indicated that vocational training and social capital should be emphasised.

The construction and validity assessment of the respiratory air quality health index (AQHI) based on the analytic hierarchy process in Tianjin, China.

BACKGROUND: Air quality health index (AQHI), as a developed air quality risk communication tool, has been proved to be more accurate in predicting air quality related health risks than air quality index (AQI) by previous studies. However, the standard method to construct AQHI is summing the excess risks of single-pollutant models directly, which may ignore the joint effect of air pollutant mixtures. METHODS: In this study, a new method which could solve the aforementioned problem, Analytic hierarchy process (AHP), was introduced. Based on this method, we constructed the respiratory health related AQHI using years of life lost (YLL) as indicator of health outcome and compared its validity with AQI. RESULTS: There was a correlation between daily AQI and AQHI in 2019 (R2 = 0.830, P < 0.01), and the chi-square test between the two excellent rates showed a statistically significant difference (χ2 = 4.156, P < 0.05). Both AQI and AQHI were correlated with the daily respiratory YLL (P < 0.01), however, the coefficient of AQHI was larger than those of AQI. CONCLUSIONS: This study indicated that compared with AQI, the constructed AQHI based on AHP may predict the health risk of air pollution more effectively. AHP may become a new method to construct AQHI which needs to be proved by taking into consideration by more studies.

A new performance evaluation indicator for the LEE Jong-wook Fellowship Program of Korea Foundation for International Healthcare to better assess its long-term educational impacts: a Delphi study.

PURPOSE: The Dr. LEE Jong-wook Fellowship Program, established by the Korea Foundation for International Healthcare (KOFIH), aims to strengthen healthcare capacity in partner countries. The aim of the study was to develop new performance evaluation indicators for the program to better assess long-term educational impact across various courses and professional roles. METHODS: A 3-stage process was employed. First, a literature review of established evaluation models (Kirkpatrick's 4 levels, CIPP model, OECD DAC criteria) was conducted to devise evaluation criteria. Second, these criteria were validated via a 2-round Delphi survey with 18 experts in training projects from May 2021 to June 2021. Third, the relative importance of the evaluation criteria was determined using the analytic hierarchy process (AHP), calculating weights and ensuring consistency through the consistency index (CI) and consistency ratio (CR), with CR values below 0.1 indicating acceptable consistency. RESULTS: The literature review led to a combined evaluation model, resulting in 4 evaluation areas, 20 items, and 92 indicators. The Delphi surveys confirmed the validity of these indicators, with content validity ratio values exceeding 0.444. The AHP analysis assigned weights to each indicator, and CR values below 0.1 indicated consistency. The final set of evaluation indicators was confirmed through a workshop with KFIH and adopted as the new evaluation tool. CONCLUSION: The developed evaluation framework provides a comprehensive tool for assessing the long-term outcomes of the Dr. LEE Jong-wook Fellowship Program. It enhances evaluation capabilities and supports improvements in the training program's effectiveness and international healthcare collaboration.

Enhancing older care services: a comprehensive internet + community home indicator system.

OBJECTIVE: Constructing a demand-oriented Internet + community home care service indicator system, starting from the actual needs of the elderly, and quantifying the demand into specific service contents that can be provided, so as to realize the effective supply of services. It aims to provide a theoretical basis for the government to formulate relevant aging policies and provide a reference basis for promoting the innovation and development of the Internet + elderly care model. METHODS: Based on existence needs, relationship needs and growth needs abbreviated as "Existence, Relatedness, Growth (ERG)" demand theory, through the discussion in the group meeting, form the expert consultation questionnaire of the demand-oriented Internet + community home care service indicator system, select experts in related fields to conduct two rounds of Delphi expert consultation, summarize the experts' opinions to determine the indicator system items, and use the Analytic Hierarchy Process (AHP) method to construct the judgment matrix to derive the weighting coefficients of the indicators, and establish the ultimate demand-oriented Internet + community home care service indicator system. RESULTS: The effective recovery rates for the two rounds of expert consoulation questionnaires were 100%, with expert authority coefficients of 0.852 and 0.868, respectively. The Kendall coefficients for the second round of expert views varied from 0.226 to 0.431, with coefficients of variation for all indexes less than 0.25.The finalized demand-oriented Internet + community home care service indicator system includes 3 first-level indicators, 10 s-level indicators, and 46 third-level indicators. The consistency ratios of indicator judgment matrices at all levels are less than 0.10, suggesting that the hierarchical analysis findings are consistent, implying that the weight coefficient distribution is appropriate. CONCLUSION: The demand-oriented Internet + community home care service Indicator System, which was created through expert consultation and AHP method, has reasonable content and is more dependable as an evaluation tool for reliably assessing demand for elderly servic.

A GIS-MCDA approach to map environmental suitability of Posidonia oceanica meadows as blue nature-based solutions in the Mediterranean eco-region.

The growing environmental risks induced by interacting climate and human-induced pressures threaten the survival and growth of marine coastal ecosystems (MCEs) and the ecosystem services they provide. Nature-based solutions (NBS), consisting of ecosystem-based approaches, have emerged as vital tools for climate adaptation and mitigation facing biodiversity loss and societal challenges. Identifying suitable environmental conditions for implementing Blue-NBS in marine coastal areas is a key priority to drive robust and cost-effective nature-based adaptation pathways. This study developed a suitability model for Blue-NBS, with a specific focus on Posidonia oceanica meadows in the Mediterranean Sea under a baseline scenario. GIS-based Multiple Criteria Decision Analysis (MCDA) was applied for data integration and prioritization of different environmental variables in geomorphological (e.g., depth), water quality (WQ) (e.g., salinity), and climatic (e.g., thermal stress) sub-groups. Suitability classes and scores for each variable were determined using statistical distributions, ensuring a data-driven approach to defining environmental suitability. Variables' weights were derived from the Analytic Hierarchy Process (AHP) based on expert judgment and then combined with scores to generate suitability maps for managing Blue-NBS on seagrasses. Depth was found to be the most dominant environmental variable, with shallow areas (e.g., Northern Adriatic, Gulf of Gabés) showing higher suitability. The southern part of the Mediterranean (e.g., Egypt) reported relatively low scores for both climate and WQ, while the Northern Adriatic had the lowest WQ scores. This study represents the first attempt to evaluate Blue-NBS suitability for seagrass meadows at the eco-regional scale with geomorphologic, WQ, and climatic variables, providing decision support for the selection and allocation of Blue-NBS in different environmental settings. The resulting environmental suitability maps represent a basis for the integration of socio-economic and governance-related indicators into a more complex, multi-tier approach to support NBS mainstreaming.

Delineating the drought vulnerability zones in Bangladesh.

The research aims to explore the vulnerability of Bangladesh to drought by considering a comprehensive set of twenty-four factors, classified into four major categories: meteorological, hydrological, agricultural, and socioeconomic vulnerability. To achieve this, the study utilized a knowledge-based multi-criteria method known as the Analytic Hierarchy Process (AHP) to delineate drought vulnerability zones across the country. Weight estimation was accomplished by creating pairwise comparison matrices for factors and different types of droughts, drawing on relevant literature, field experience, and expert opinions. Additionally, online-based interviews and group discussions were conducted with 30 national and foreign professionals, researchers, and academics specializing in drought-related issues in Bangladesh. Results from overall drought vulnerability map shows that the eastern hills region displays a notably high vulnerability rate of 56.85% and an extreme low vulnerability rate of 0.03%. The north central region shows substantial vulnerability at high levels (35.85%), while the north east exhibits a significant proportion (41.68%) classified as low vulnerability. The north west region stands out with a vulnerability rate of 40.39%, emphasizing its importance for drought management strategies. The River and Estuary region displays a modest vulnerability percentage (38.44%), suggesting a balanced susceptibility distribution. The south central and south east regions show significant vulnerabilities (18.99% and 39.60%, respectively), while the south west region exhibits notable vulnerability of 41.06%. The resulting model achieved an acceptable level of performance, as indicated by an area under the curve value of 0.819. Policymakers and administrators equipped with a comprehensive vulnerability map can utilize it to develop and implement effective drought mitigation strategies, thereby minimizing the losses associated with drought.

Integrated Approach Using Intuitionistic Fuzzy Multicriteria Decision-Making to Support Classifier Selection for Technology Adoption in Patients with Parkinson Disease: Algorithm Development and Validation.

Background: Parkinson disease (PD) is reported to be among the most prevalent neurodegenerative diseases globally, presenting ongoing challenges and increasing burden on health care systems. In an effort to support patients with PD, their carers, and the wider health care sector to manage this incurable condition, the focus has begun to shift away from traditional treatments. One of the most contemporary treatments includes prescribing assistive technologies (ATs), which are viewed as a way to promote independent living and deliver remote care. However, the uptake of these ATs is varied, with some users not ready or willing to accept all forms of AT and others only willing to adopt low-technology solutions. Consequently, to manage both the demands on resources and the efficiency with which ATs are deployed, new approaches are needed to automatically assess or predict a user's likelihood to accept and adopt a particular AT before it is prescribed. Classification algorithms can be used to automatically consider the range of factors impacting AT adoption likelihood, thereby potentially supporting more effective AT allocation. From a computational perspective, different classification algorithms and selection criteria offer various opportunities and challenges to address this need. Objective: This paper presents a novel hybrid multicriteria decision-making approach to support classifier selection in technology adoption processes involving patients with PD. Methods: First, the intuitionistic fuzzy analytic hierarchy process (IF-AHP) was implemented to calculate the relative priorities of criteria and subcriteria considering experts' knowledge and uncertainty. Second, the intuitionistic fuzzy decision-making trial and evaluation laboratory (IF-DEMATEL) was applied to evaluate the cause-effect relationships among criteria/subcriteria. Finally, the combined compromise solution (CoCoSo) was used to rank the candidate classifiers based on their capability to model the technology adoption. Results: We conducted a study involving a mobile smartphone solution to validate the proposed methodology. Structure (F5) was identified as the factor with the highest relative priority (overall weight=0.214), while adaptability (F4) (D-R=1.234) was found to be the most influencing aspect when selecting classifiers for technology adoption in patients with PD. In this case, the most appropriate algorithm for supporting technology adoption in patients with PD was the A3 - J48 decision tree (M3=2.5592). The results obtained by comparing the CoCoSo method in the proposed approach with 2 alternative methods (simple additive weighting and technique for order of preference by similarity to ideal solution) support the accuracy and applicability of the proposed methodology. It was observed that the final scores of the algorithms in each method were highly correlated (Pearson correlation coefficient >0.8). Conclusions: The IF-AHP-IF-DEMATEL-CoCoSo approach helped to identify classification algorithms that do not just discriminate between good and bad adopters of assistive technologies within the Parkinson population but also consider technology-specific features like design, quality, and compatibility that make these classifiers easily implementable by clinicians in the health care system.

Constructing a Competency Training Index System in Public Health Emergencies for Community Nurses.

OBJECTIVE: A competency training index system was designed in public health emergencies for community nurses. The purpose of this approach is to provide community nurses with guidelines for standardized training programs on how to respond to public health emergencies. METHODS: Through semi-structured interviews, a literature review, and team discussion, the first draft of competency training index system in public health emergencies for community nurses was formed. The Delphi method was used for two rounds of expert consultation to screen, modify and determine indicators. Finally, the analytic hierarchy process was utilized to calculate the weights of indicators at all levels. RESULTS: A total of 15 expert consultants were included. The effective recovery rate of the two rounds of expert consultation questionnaire was 100%, the expert authority coefficient was 0.880, 0.887, and the Kendall coordination coefficient was 0.172 and 0.171 (p < 0.001). Expert opinions have determined that the final revised competency index system in public health emergencies for community nurses training consists of 2 primary indicators, 10 secondary indicators, and 46 tertiary indicators. CONCLUSION: The study has developed a competency training index system in public health emergencies for community nurses. This system can serve as a foundation for standardized training in community health service institutions. It is characterized by its high demand, scientific approach, reliability, and rationality.

Addressing integration in the organization of palliative care in belgium: a multilevel ecosystems approach using the analytic hierarchy process (AHP) method.

BACKGROUND: Palliative care is becoming an essential component of healthcare, but there is insufficient research on how integration across different levels of care (micro, meso, and macro) is realized in practice. Without such integration, care may become fragmented, leading to suboptimal patient outcomes. While many studies have explored palliative care models, there is a gap in understanding how priorities for integrated care align across these levels within healthcare ecosystems. Specifically, it is unclear whether key actions at each level are shared, coordinated, and supported effectively, making it difficult to implement sustainable, cohesive care strategies. Our study aims to explore the extent to which important goals (i.e., priorities) are shared across the micro, meso, and macro levels of the palliative care ecosystem in Flanders, Belgium. METHODS: We applied a multimethod study using the analytic hierarchy process method (AHP). This consists of three sequential steps: a broad literature search and interviews with Belgian stakeholders (n = 12) to determine the criteria for the organization of integrated care; focus groups (n = 8) with patients, their relatives and caregivers to establish the completeness and relevance of the criteria; and prioritization of the criteria using a questionnaire among 305 Flemish participants (patients, relatives, caregivers and policy makers). RESULTS: Our findings revealed that integration is imbalanced, with priorities being most emphasized at the micro level (57%), followed by the meso (29%) and macro (14%) level. Functional enablers dominate at the macro (80%) and meso organizational level (67%), while normative enablers are emphasized at the meso professional (67%) and micro level (75%). Effective palliative care requires vertical coordination of these enablers: for instance, transparent communication with patients at the micro level depends on cross-organizational information exchange at the meso level, supported by a unified data system at the macro level. CONCLUSION: Achieving integrated palliative care requires deliberate alignment of priorities across all levels of the ecosystem. While each level plays a unique role, palliative care is comprehensive and effective only by sharing both functional and normative enablers across micro, meso, and macro level.

Locating the suitable large-scale solar farms in China's deserts with environmental considerations.

Desert areas offer rich solar resources and low land use costs, ideal for large-scale new energy development. However, desert ecosystems are fragile, and large-scale photovoltaic (PV) power facilities pose ecological risks. Current assessments of PV plant sites in deserts lack consideration of wind-sand hazards and ecological impacts. In this study, we have developed a new large-scale photovoltaic (PV) site selection model that integrates the analytic hierarchy process with geographic information system technology, and applies it to the desert regions of China. The results show that the potential for large-scale PV power plants in China's deserts is significant, with 69.4 % of the region assessed as medium or higher. The most suitable area is 12.7 × 104 km2 (7.6 % of the overall study area), mainly centered in the Tibetan Plateau's Qaidam Basin Desert and the deserts of northern China, characterized by favorable solar resources, climate, and terrain. Across all regions, gravel deserts are recognized as more suitable for the construction of large-scale PV power projects than sandy deserts. Considering varying PV installation density scenarios with an installed capacity potential of 36.4-84.9 TW and system costs ranging from 10.0 to 33.5 trillion USD, the study estimates an annual solar power generation potential of 47-110 PWh which is 1.7-3.9 times the global electricity demand. Carbon emissions could be reduced by 26.8-62.6 gigatons annually, offsetting 73-170 % of global emissions. Covering just 4.8-11.5 % of China's desert area (8 × 104-19.4 × 104 km2) would meet the projected 2025 electricity needs of the country. This study lays the groundwork for spatial planning and benefit assessment of large-scale PV projects in desert regions, and reduces conflicts between PV plant construction and local ecosystem.

Identifying optimal locations for the development of health facilities towards the attainment of universal health coverage using geospatial techniques in Kishapu district, Tanzania.

Two hours of travel time specified by the World Health Organization (WHO) to access quality health services is among the most important criteria for the Universal Health Coverage. However, locations of health facilities (HF) in many developing countries fail to realise this target due to a lack of appropriate models considering the local environment. This work used the central-place theory to explore locations of HF in Kishapu and their accessibility status based on two means of transport in the AccessMod tool: walking only and the combination of walking-and-motor devices. The results of the walking scenario indicated that the travel times to the health centres and hospitals exceeded 2 h, and a direct relationship existed between the facility level and the travel time spent to access it. The combined transport (walking and motorized) showed that dispensaries are easily accessible (14.5 min) compared to health centres (42.8 min) and hospitals (67.3 min). To address the challenge, we have developed a model revealing optimal sites with quick access for HF construction and improvement using Multi-Criteria-Evaluation and Analytical-Hierarchy Process methods weighting five criteria including distance from settlements (44% weight), roads (26% weight), existing health facilities (16% weight), rivers (9% weight) and railway (5% weight). A test of the model with both means of transport shows that at all places proposed to be optimal allow patitents to travel in less than 2 h, indicating that the proposed model can effectively and efficiently solve the challenge of allocating HF in society.

Megacity solid waste disposal suitability mapping in Dhaka, Bangladesh: an integrated approach using remote sensing, GIS and statistics.

Selecting suitable Megacity Solid Waste Disposal (MSWD) sites is a challenging task in densely populated deltas of developing countries, exacerbated by limited public awareness about waste management. One of the major environmental concerns in Dhaka City, the world's densest megacity, is the presence of dumps close to surface water bodies resources. This study employed the Geographic Information System (GIS)-Analytic Hierarchy Process (AHP) framework to integrate geomorphological (slope and flow accumulation), geological (lithological and lineament), hydrogeological (depth to groundwater table and surface waterbody), socioeconomic (Land use land cover, distance to settlement, road, and airport), and climatological (wind direction) determinants, coupled by land-use and hydro-environmental analyses, to map optimal dumps (MSWDO) sites. The resulting preliminary (MSWDP) map revealed 15 potential landfill areas, covering approximately 5237 hectares (ha). Combining statistical analysis of restricted areas (settlements, water bodies, land use) with AHP-based ratings, the MSWDO map revealed two optimal locations (2285 ha). Additionally, the hydro-environmental analysis confirmed the unsuitability of northern sites due to shallow groundwater (< 5.43 m) and thin clay, leaving 11 options excluded. Sites 12 (Zone A, 2255 ha) and 15 (Zone B, 30 ha), with deeper groundwater tables and thicker clay layers, emerged as optimal choices for minimizing environmental risks and ensuring effective long-term waste disposal. This study successfully integrates remote sensing, geospatial data, and GIS-AHP modeling to facilitate the development of sustainable landfill strategies in similar South Asian delta megacities. Such an approach provides valuable insights for policymakers to implement cost-effective and sustainable waste management plans, potentially minimizing the environmental risks to achieve Sustainable Development Goals (SDGs) 6, 11, 13, and 15.

Optimizing Nutritional Decisions: A Particle Swarm Optimization-Simulated Annealing-Enhanced Analytic Hierarchy Process Approach for Personalized Meal Planning.

BACKGROUND/OBJECTIVE: Nutritionists play a crucial role in guiding individuals toward healthier lifestyles through personalized meal planning; however, this task involves navigating a complex web of factors, including health conditions, dietary restrictions, cultural preferences, and socioeconomic constraints. The Analytic Hierarchy Process (AHP) offers a valuable framework for structuring these multi-faceted decisions but inconsistencies can hinder its effectiveness in pairwise comparisons. METHODS: This paper proposes a novel hybrid Particle Swarm Optimization-Simulated Annealing (PSO-SA) algorithm to refine inconsistent AHP weight matrices, ensuring a consistent and accurate representation of the nutritionist's expertise and client preferences. Our approach merges PSO's global search capabilities with SA's local search precision, striking an optimal balance between exploration and exploitation. RESULTS: We demonstrate the practical utility of our algorithm through real-world use cases involving personalized meal planning for individuals with specific dietary needs and preferences. Results showcase the algorithm's efficiency in achieving consistency and surpassing standard PSO accuracy. CONCLUSION: By integrating the PSO-SA algorithm into a mobile app, we empower nutritionists with an advanced decision-making tool for creating tailored meal plans that promote healthier dietary choices and improved client outcomes. This research represents a significant advancement in multi-criteria decision-making for nutrition, offering a robust solution to the inconsistency challenge in AHP and paving the way for more effective and personalized dietary interventions.

Establishing an Evaluation Indicator System for User Satisfaction With Hypertension Management Apps: Combining User-Generated Content and Analytic Hierarchy Process.

BACKGROUND: Hypertension management apps (HMAs) can be effective in controlling blood pressure, but their actual impact is often suboptimal. Establishing a user satisfaction evaluation indicator system for HMAs can assist app developers in enhancing app design and functionality, while also helping users identify apps that best meet their needs. This approach aims to improve the overall effectiveness of app usage. OBJECTIVE: This study aims to systematically collect data on HMAs and their user reviews in the United States and China. It analyzes app usage patterns and functional characteristics, identifies factors influencing user satisfaction from existing research, and develops a satisfaction evaluation indicator system to provide more accurate recommendations for improving user satisfaction. METHODS: We conducted a descriptive statistical analysis to assess the development status of HMAs in both countries and applied the task-technology fit model to evaluate whether the app functionalities align with business needs. We separately summarized the factors influencing user satisfaction in both countries from previous research, utilized the analytic hierarchy process to develop an evaluation indicator system for HMA user satisfaction, and calculated satisfaction levels. Based on these findings, we propose improvements to enhance app functionality and user satisfaction. RESULTS: In terms of current development status, there were fewer HMAs and user reviews in China compared with the United States. Regarding app functional availability, fewer than 5% (4/91) of the apps achieved a demand fulfillment rate exceeding 80% (8/10). Overall, user satisfaction in both countries was low. CONCLUSIONS: In the United States, user satisfaction was lowest for advertising distribution, data synchronization, and reliability. By contrast, Chinese apps need improvements in cost efficiency and compatibility.

Factors affecting small dental business in rural Germany: Evidence from Hessen.

OBJECTIVES: To determine how social factors influence career decisions of dental service providers, particularly focusing on examining the impact of dentists' origins. METHODS: Online survey of Hessian panel dentists, with pairwise comparisons to a set of factors impacting their decision-making process. An Analytic Hierarchy Process examined the weighting of influencing drivers in career choice. RESULTS: Dentists from rural backgrounds were more likely to establish practices in rural areas than those from urban origins. Origin correlated with entrepreneurial intentions and a strong association of rural origin. Dentists who grew up in rural areas were 4.19 times more likely to start a business. CONCLUSION: These findings may support efficient resource allocation and support for rural dental businesses.

Developing an assessment tool for the healthy lifestyles of the occupational population in China: a modified Delphi-analytic hierarchy process study.

Lifestyle is an important factor affecting people's health. Evaluating and promoting healthy lifestyles among occupational population can not only improve work ability and efficiency, but also contribute to the prevention a variety of potential diseases. This study developed a preliminary index system based on literature review and group discussion. Two rounds of expert consultation were conducted on 12 experts using Delphi method. The questionnaire recovery rate of the two rounds of Delphi survey was over 85%, the expert authority coefficient was over 0.70, and Kendall W was 0.450 and 0.446, which were significant (P < 0.001). The weighting coefficient of each indicator was calculated using the hierarchical analysis method. Among them, the weighting coefficients of physical health lifestyle, mental health lifestyle, social adaptation lifestyle and occupational health lifestyle were 0.4133, 0.2922, 0.1078 and 0.1867, respectively. The consistency index CI = 0.024 and the consistency ratio CR = 0.027 of the first-level index judgment matrix. The weighting coefficient is acceptable and the indicators do not cause logical confusion. The healthy lifestyle assessment tool of the occupational population constructed in this study consists of 4 primary indicators, 13 secondary indicators and 45 tertiary indicators, which can provide a standardized and operable assessment tool for monitoring and evaluating the healthy lifestyle of the Chinese occupational population. At the same time, the weight analysis of various indicators through the analytic hierarchy process can also provide reference for the key areas of occupational health intervention.

Enhancing biometric system selection: A hybrid AHP-neutrosophic fuzzy TOPSIS approach.

A biometric system is essential in improving security and authentication processes across a variety of fields. Due to multiple criteria and alternatives, selecting the most suitable biometric system is a complex decision. We employ a hybrid approach in this study, combining the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) with the Analytic Hierarchical Process (AHP). Biometric technologies are ranked using the TOPSIS method according to the relative weights that AHP determines. By applying the neutrosophic set theory, this approach effectively handles the ambiguity and vagueness inherent in decision-making. Fingerprint, face, Iris, Voice, Hand Veins, Hand geometry and signature are the seven biometric technologies that are incorporated in the framework. Seven essential characteristics are accuracy, security, acceptability, speed and efficiency, ease of collection, universality, distinctiveness used to evaluate these technologies. The model seeks to determine which biometric technology is best suited for a particular application or situation by taking these factors into account. This technique may be applied in other domains in the future.

Enhancing cassava grater design: A customer-driven approach using AHP, QFD, and TRIZ integration.

Due to consistent cassava cultivation, small-scale processing centers rely heavily on the cassava grater. However, these machines face stagnation in innovation and design evolution, leading to inefficiencies, limited capacity, and inconsistent output. Adding to these challenges is the competitive global market, demanding a focus on design enhancements. This study employs a multi-faceted approach involving the Analytic Hierarchy Process (AHP), Quality Function Deployment (QFD) and Theory of Inventive Problem Solving (TRIZ) to prioritize customer requirements, propose technically aligned solutions, and offer innovative design options for cassava graters. A total of 10 customer requirements (CR), 21 technical solutions (TS), and 63 innovative design options (IDO) were established and prioritized, aiming for easy adoption by fabricators, engineers, manufacturers, and artisans. Implementing these insights boosts cassava grater efficiency and productivity and significantly advances knowledge. This work presents a thorough scientific framework for product design, empowering local manufacturers to remain viable and relevant in the rapidly changing field of product enhancement.

Urban flooding simulation and flood risk assessment based on the InfoWorks ICM model: A case study of the urban inland rivers in Zhengzhou, China.

Urban flooding intensifies with escalating urbanization. This study focuses on Xiong'er river as the study area and couples a 1D/2D urban flooding model using InfoWorks ICM (Integrated Catchment Modeling). Ten scenarios are set respectively with a rainfall return period of 5a 10a, 20a, 50a, and 100a, alongside rainfall durations of 1 and 24 h. Subsequently, the H-V (hazard-vulnerability) method was applied to evaluate urban flooding risk. Three indicators were selected for each of hazard factors and vulnerability factors. The relative weight values of each indicator factor were calculated using the AHP method. The result shows that (1) flood depth, rate, and duration escalate with longer rainfall return periods, yet decrease as the duration of rainfall increases; (2) as the rainfall return period lengthens, the proportion of node overflow rises, whereas it diminishes with longer rainfall durations, leading to an overall overloaded state in the pipeline network; and (3) the distribution in the research area is mainly low-risk areas, with very few extremely high-risk. Medium to high-risk areas are mainly distributed on both sides of the river, in densely built and low-lying urban areas. This study demonstrates that the model can accurately simulate urban flooding and provide insights for flood analyses in comparable regions.