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Coastal hazards are an urgent issue of global concern considering the increasing population pressure in coastal regions, retreating coastlines, and rising seawater levels. Here we demonstrate the process of assessing the vulnerability of a coastal urban environment using the case of Kuala Terengganu, a coastal town in Malaysia, and evaluating the potential social, environmental, and economic impacts. Uncertainties in the human dimensions of global change deeply affect the assessment and responses to environmental, climatic, and non-climate impacts on coastal city population growth and communities. We address these uncertainties by combining a Delphi-Analytical Hierarchy Process (Delphi-AHP) model and Geographic Information System (GIS)tools to determine mitigation and adaptation probabilities as part of a Coastal City Vulnerability Assessment. We conclude by presenting calculations of the short- and long-term suitability for land use and recommending hazard mitigation measures to equip city planners and decision-makers in evaluating hazards and potential impacts on coastal city areas.

Globally, the pandemic of COVID-19 has penetrated all spheres of human endeavors, and noteworthy is the tremendous increase in the volume of healthcare wastes generated in Nigeria. There has been an increase in medical waste materials produced as a result of the extensive use of both disposable personal protective equipment (PPE), such as face shields and nose and face masks, and highly infectious waste materials, such as contaminated syringes, needles, and soiled bandages from diagnosed positive cases. Despite the huge volume in waste generation, a standardized evaluation framework is currently lacking in the management of medical wastes in Nigeria. This study has developed a novel assessment framework for managing medical wastes, which is curated from the technical guidelines of the World Health Organization (WHO). The applicability of the framework was examined on seven designated public and private-owned hospitals in Ota. The fuzzy analytical hierarchy process (FAHP) and analytical hierarchy process (AHP) approaches of multi-criteria decision analysis were utilized in modelling an evaluation framework for the objective of medical waste management. Carefully designed interview questionnaires, observations, and site visits were carried out to obtain data from healthcare professionals in Ota. Results show that waste segregation was practiced more decisively in private hospitals than public hospitals. Waste segregation is established as a key determinant in implementing an effective waste management system in any healthcare facility. The success of waste segregation in healthcare institutions is highly dependent on good hospital management, organizational policies, efficient budget planning for waste management, and the operational running cost. Disposal methods investigated were mostly open burning and incessant dumping for most public health care centers. Deficient waste management practices were observed in waste disposal, waste transportation, storage, and organizational policies. While the awareness and capacity building on occupational safety practices and environmental public health is widely known by health workers and waste handlers, compliance and enforcement are critical challenges. The validation of results using fuzzy TOPSIS and a sensitivity analysis shows a high degree of the consistency, stability, and robustness of the model. Findings from the present study can aid decision making, as this will benefit policy makers and key stakeholders in developing more comprehensive and effective medical waste management guidelines in Nigeria. In addition, future decision-making studies could augment the results from the current research by assessing the impact of the pandemic preparedness and response on medical waste management.

Water resource ecological safety is a key factor in regional economic and social development. The comprehensive evaluation of water resource ecological safety is an important precondition for realizing regional sustainable development with the increasingly serious water ecological crisis. Zhoushan City of China was taken as an example, and the pressure-state-response model (PSR) was used to evaluate the ecological safety status of regional water resources, improve deficiencies in the existing evaluation index system and evaluation method effectively, and put forward three evaluation subsets (18 evaluation indexes). An evaluation index system was established based on these indexes to evaluate the water resource ecological safety. Combined weights of indexes were calculated using the analytic hierarchy process (AHP) and entropy weight method, and water-resource ecological safety indexes were used to evaluate the water-resource ecological safety status in Zhoushan City during 2010-2019. Results show that the water-resource ecological safety level in Zhoushan City during 2010-2019 presents a rising trend and transformed from a serious warning state into a medium warning state as well as a relatively safe state and safe state. This transformation indicates that the ecological safety status in Zhoushan City gradually improves. The comprehensive evaluation value is the minimum (0.15) under the serious warning state in 2013 and the maximum (0.85) under the safe state in 2019. Ammonia nitrogen and chemical oxygen demand (COD) emissions in industrial wastewater, total water supply throughout the year, and governance area of water and soil loss are the main factors that influence the water resource ecological safety in the city. The ecological safety level of regional water resources can be effectively elevated through key measures, such as increasing the water resource supply throughout the year, reducing the application of pesticides and chemical fertilizers, and reducing the discharge of pollutants, including COD and ammonia nitrogen in industrial wastewater. The water resource ecological safety evaluation model based on the PSR model and AHP-entropy weight method that demonstrates a certain application value can provide a novel idea and method to support the ecological safety evaluation of regional water resources.

Global pandemics, such as the Coronavirus Disease 2019 (COVID-19), have serious harmful effects on people′s physical health and mental well-being. It is imperative therefore that we seek to understand community resilience and identify ways to enhance this, especially within our cities and communities. Therefore, great emphasis is now placed on how cities prepare for and recover from such disasters, and community resilience has emerged as a key consideration. Drawing upon research on the theory of resilience, this study seeks to identify the factors that influence community resilience and to analyze their causation toward helping to manage the risks associated with the COVID-19 pandemic. Seventeen factors from the five dimensions of social capital, economic capital, physical environment, demographic characteristics, and institutional factors are used to construct an index system. This is used to establish the structural level and importance of each factor. Data were collected using a questionnaire survey involving 12,000 members of key community groups in the city of Wuhan. An interpretative structural model (ISM) combining the analytic hierarchy process (AHP) method was then used to obtain the multi-level hierarchical structure composed of direct factors, indirect factors, and fundamental factors. The results show that the income level, vulnerability of the population, and the built environment are the main factors that affect the resilience of communities affected by COVID-19. These findings provide useful guidance toward the effective planning and design of urban construction and infrastructure. The results are expected to be useful to inform future decision-making and toward the long term, sustainable management of the risks posed by COVID-19.

Landslides and slope instabilities are major risks for human activities which often lead to economic losses and human fatalities all over the world. The main purpose of this study is to evaluate and compare the results of Landslide Nominal Risk Factor (LNRF), Frequency Ratio (FR), and Analytical Hierarchy Process (AHP) models in mapping Landslide Susceptibility Index (LSI). The study case, Nojian watershed with an area of 344.91 km2, is located in Lorestan province of Iran. The procedure was as follows: first, the effective factors of the landslide basin were prepared for each layer in the GIS software. Then, the layers and the landslides of the basin were also prepared using aerial photographs, satellite images, and fieldwork. Next, the effective factors of the layers were overlapped with the map of landslide distribution to specify the role of units in such distribution. Finally, nine factors including lithology, slope, aspect, altitude, distance from the fault, distance from river, fault land use, rainfall, and altitude were found to be effective elements in landslide occurrence of the basin. The final maps of LSI were prepared based on seven factors using LNRF, FR, and AHP models in GIS. The index of the quality sum (Qs) was also used to assess the accuracy of the LSI maps. The results of the three models with LNRF (40%), FR (39%), and AHP (44%) indicated that the whole study area was located in the classes of high to very high hazard. The Qs values for the three models above were also found to be 0.51, 0.70 and 0.70, respectively. In comparison, according to the amount of Qs, the results of AHP and FR models have slightly better performed than the LNRF model in determining the LSI maps in the study area. Finally, the study watershed was classified into five classes based on LSI as very low, low, moderate, high, and very high. The landslide susceptibility maps can be helpful to select sites and mitigate landslide hazards in the study area and the regions with similar conditions.

Sustainable supplier selection (SSS) is gaining popularity as a practical method to supply chain sustainability among academics and practitioners. However, in addition to balancing economic, social, and environmental factors, the emergence of the COVID-19 pandemic has affected the selection of long-term suppliers to ensure sustainable supply chains, recover better from the pandemic and effectively respond to any future unprecedented crises. The purpose of this study is to assess and choose a possible supplier based on their capability to adapt to the COVID-19 epidemic in a sustainable manner. For this assessment, a framework based on multi-criteria decision making (MCDM) is provided that integrates spherical fuzzy Analytical Hierarchical Process (SF-AHP) and grey Complex Proportional Assessment (G-COPRAS), in which spherical fuzzy sets and grey numbers are used to express the ambiguous linguistic evaluation statements of experts. In the first stage, the evaluation criteria system is identified through a literature review and experts’ opinions. The SF-AHP is then used to determine the criteria weights. Finally, the G-COPRAS method is utilized to select sustainable suppliers. A case study in the automotive industry in Vietnam is presented to demonstrate the proposed approach’s effectiveness. From the SF-AHP findings, “quality”, “use of personal protective equipment”, “cost/price”, “safety and health practices and wellbeing of suppliers”, and “economic recovery programs” have been ranked as the five most important criteria. From G-COPRAS analysis, THACO Parts (Supplier 02) is the best supplier. A sensitivity study was also conducted to verify the robustness of the proposed model, in which the priority rankings of the best suppliers are very similar. For long-term development and increased competitiveness, industrial businesses must stress the integration of response mechanisms during SSS implementation in the COVID-19 epidemic, according to the findings. This will result in significant cost and resource savings, as well as reduced environmental consequences and a long-term supply chain, independent of the crisis.

Cloud computing is a style of computing which thrives users requirements by delivering scalable, on-demand and pay-per-use IT services. It offers different service models, out of which Storage as a Service (StaaS) is the fundamental block of Infrastructure cloud that fulfills user’s excess demand of elastic computing resources.  But considering the competitive business scenario choosing the best cloud storage provider is a difficult task. Thus, usability is considered to be the key performance indicator which evaluates the better cloud storage based on user’s satisfaction. This paper aims to focus on the usability evaluation of StaaS providers namely Google drive, Drop box and One drive. This paper proposed a fuzzy based AHP model for measuring user satisfaction. Usability evaluation is carried out based on user feedback through Interview and Questionnaire method. Analysis of user feedback is done based on the fuzzy approach in order to remove vaguness. Whereas, AHP model is used for measuring satisfaction degree of the different cloud storage services and it solves the problem of selecting best cloud storage.

Landslides are among the most critical geo-environmental disasters for both humans and the environment. This study intended to create a landslide susceptibility map (LSM) for the Akre District of Kurdistan Region, Northern Iraq. In this paper, 15 landslide causative criteria including elevation, slope, curvature, aspect, topographic wetness index, topographic roughness index, steam power index, lithology, lineament density, soil types, land use/cover, normalized difference vegetation index, distance to roads, rainfall, and distance to streams were analysed. For this purpose, frequency ratio (FR), analytic hierarchy process (AHP), and ensemble FR-AHP models based on geoinformatics techniques were applied. The LSMs were then assigned into five categories based on their susceptibility levels: very low, low, medium, high, and very high. The results showed that the high and very high landslide susceptibility categories for the FR, AHP, and hybrid FR-AHP models were 27.75% (732,01 km 2 ), 28.44% (750,36 km 2 ), and 28.84% (761 km 2 ), respectively. The results showed that the majority of historical landslide incidents occurred in mountainous terrain in the northern parts of the study area, which are classified as high and very high susceptibility zones. The predicted rate curves for the FR, AHP, and hybrid FR-AHP models had areas under curve of the receiver operating characteristic curve (AUC-ROC) values of 93.4%, 89.3%, and 93.8%, respectively, which indicate that the ensemble FR-AHP model provides more reliable and accurate results for LSM. The LSM generated via the hybrid FR-AHP model can be utilised by local authorities, managers, and decision-makers in further land use/cove planning to mitigate the devastating influences of landslides in the area.

The theoretical methods of humanistic care and scenario-based design are widely used in various urban construction designs. Based on the concept of humanistic care, this study conducts an in-depth research on the public space design of urban renewal projects and proposes a model for evaluating humanistic care. An emotion measurement method is proposed to comprehensively analyze subjective and objective emotion indicators using principal component analysis and Pearson correlation to realize the quantitative measurement and examination of humanistic care construction of public space. Combining AHP and Kano model to construct the humanistic care evaluation index system of public space design, defining the primary and secondary criteria of humanistic care in public space, and calculating the comprehensive evaluation score of humanistic care. Taking S City Riverside Park as the research object, we conducted an evaluation and analysis of the humanistic care construction of public spaces. The subject tourists showed less changes in systolic and diastolic blood pressure indexes at the end of the tour, while the average heart rate decreased from 73.16 to 68.72 before the experiment, showing a significant difference (P=0.004<0.01). Positive mood scale and score scale scores showed significant differences (P<0.05), while negative mood scale did not show significant differences (P>0.05). The humanistic care evaluation index system evaluation has a final score of 3.5045, and the humanistic care environment in public space is not sufficient. Aiming at the humanistic care construction problems of public space faced by the urban renewal project represented by the S City Riverside Park, a coping strategy is proposed.

Colleges and universities often focus on cultivating talent, a practice that directly contributes to the lack of creativity among their students. In light of this, this paper aims to promote education reform and enhance students’ capacity for innovation. This paper constructs the evaluation index system and model of innovation ability of students in colleges and universities to promote the cultivation of innovative talents. Based on the AHP model to determine the index weight of each evaluation factor, with the help of gray correlation to analyze the relationship of each evaluation index, the decision matrix is established, and the gray comprehensive judgment model is constructed. We establish the evaluation sample matrix by using the whitened weight function to determine the evaluation gray class. We then calculate the gray evaluation coefficients, weight vectors, and weight matrices to arrive at a comprehensive evaluation of innovative ability. This paper employs the Hebei University of Technology in China as its research site and applies its methodology to evaluate the innovation capacity of its students. The comprehensive evaluation value of the students’ innovative abilities is only 6.67, placing them at the medium level. The maximum relative error between the evaluation mean value of each specific index at the index level and the expert evaluation result is 1.84%. In terms of the satisfaction of the evaluation method, the satisfaction mean value of this paper’s method exceeds that of the expert evaluation method in the dimensions of the evaluation concept, the evaluation subject, the evaluation method, the evaluation indexes, the evaluation procedure, and the application of the evaluation result, which are respectively 0.14, 1.25, 1.43, 0.7, 1.45, and 0.49.