Developing a risk assessment tool for cancer-related venous thrombosis in China: a modified Delphi-analytic hierarchy process study.

OBJECTIVE: To develop a Risk Assessment Tool for Cancer-related Venous Thrombosis in China. METHODS: A modified two-round Delphi method was employed to establish consensus within a field to reach an agreement via a questionnaire or by interviewing a multidisciplinary panel of experts by collecting their feedback to inform the next round, exchanging their knowledge, experience, and opinions anonymously, and resolving uncertainties. Furthermore, The AHP (Analytic Hierarchy Process) was used to determine the final quality indicators' relative importance. RESULTS: The expert's positive coefficient was 85.19% in the first round and 82.61% in the second round, with authoritative coefficients of 0.89 and 0.92 in the respective surveys. The P-value of Kendall's W test was all less than 0.001 for each round, and the W-value for concordance at the end of the two rounds was 0.115. The final Risk Assessment Tool for Cancer-related Venous Thrombosis consisted of three domains, ten subdomains, and 39 indicators, with patient factors weighing 0.1976, disease factors weighing 0.4905, and therapeutic factors weighing 0.3119. CONCLUSION: The tool is significantly valid and reliable with a strong authority and coordination degree, and it can be used to assess the risk of cancer-related VTE and initiate appropriate thrombophylactic interventions in China.

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.

Study on the Association between anterior tooth Colour Preference based on the FAHP and individual factors.

BACKGROUND: The relationship between tooth colour and individual satisfaction in oral aesthetics has long been a topic of interest. In this study, we utilized the fuzzy analytic hierarchy process (FAHP) to investigate the impacts of sex and age on tooth colour preference. The findings of this study should provide a scientific basis for oral aesthetic practice. METHODS: In the current study, a random selection method was employed, and a survey was completed by 120 patients. To obtain tooth colour data, standard tooth colour charts were used. Smile photos were taken as template images using a single-lens reflex camera. The FAHP was utilized to conduct a weight analysis of tooth colour preferences among patients of different sexes and age groups. RESULTS: There were significant differences in tooth colour preference based on sex and age. Men tend to prefer the B1 colour, while women may prioritize the aesthetic effects of other colours. Additionally, as patients age, their preferences for tooth colour become more diverse. These findings offer valuable insights for oral aesthetics practitioners, enabling them to better address the aesthetic needs of patients across different sexes and ages. This knowledge can aid in the development of more personalized treatment plans that align with patients' expectations. CONCLUSION: In this study, we utilized scientific analysis methods to quantify the popularity of different tooth colours among various groups of people. By doing so, we established a scientific foundation for clinical practice. The findings of this study offer valuable insights for oral aesthetic research, enhancing our understanding of tooth colour. Additionally, these findings have practical applications in the field of oral medicine, potentially improving patients' quality of life and overall oral health.

Constructing an evaluation index system for clinical nursing practice teaching quality using a Delphi method and analytic hierarchy process-based approach.

BACKGROUND: The key step in evaluating the quality of clinical nursing practice education lies in establishing a scientific, objective, and feasible index system. Current assessments of clinical teaching typically measure hospital learning environments, classroom teaching, teaching competency, or the internship quality of nursing students. As a result, clinical evaluations are often insufficient to provide focused feedback, guide faculty development, or identify specific areas for clinical teachers to implement change and improvement. Therefore, the purpose of our study was to to construct a scientific, systematic, and clinically applicable evaluation index system of clinical nursing practice teaching quality and determine each indicator's weight to provide references for the scientific and objective evaluation of clinical nursing practice teaching quality. METHODS: Based on the "Structure-Process-Outcome" theoretical model, a literature review and Delphi surveys were conducted to establish the evaluation index system of clinical nursing practice teaching quality. Analytic Hierarchy Process (AHP) was employed to determine the weight of each indicator. RESULTS: The effective response rate for the two rounds of expert surveys was 100%. The expert authority coefficients were 0.961 and 0.975, respectively. The coefficient of variation for the indicators at each level ranged from 0 to 0.25 and 0 to 0.21, and the Kendall harmony coefficients were 0.209 and 0.135, respectively, with statistically significant differences (P < 0.001). The final established index system included 3 first-level, 10 second-level, and 29 third-level indicators. According to the weights computed by the AHP, first-level indicators were ranked as "Process quality" (39.81%), "Structure quality" (36.67%), and "Outcome quality" (23.52%). Among the secondary indicators, experts paid the most attention to "Teaching staff" (23.68%), "Implementation of teaching rules and regulations (14.14%), and "Teaching plans" (13.20%). The top three third-level indicators were "Level of teaching staff" (12.62%), "Structure of teaching staff" (11.06%), and "Implementation of the management system for teaching objects" (7.54%). CONCLUSION: The constructed evaluation index system of clinical nursing practice teaching quality is scientific and reliable, with reasonable weight. The managers' focus has shifted from outcome-oriented to process-oriented approaches, and more focus on teaching team construction, teaching regulations implementation, and teaching design is needed to improve clinical teaching quality.

Safety Evaluation for Fabricated Small Box Girder Bridges Based on Fuzzy Analytic Hierarchy Process and Monitoring Data.

During the operation of fabricated small box girder bridges, which face safety issues such as structural degradation and failure, there is an urgent need to propose a safety evaluation method to cope with the possible risks. This article quantitatively evaluates the safety state of a fabricated small box girder bridge in Wuhan City based on Fuzzy Analytic Hierarchy Process (FAHP) and structural health monitoring (SHM) data. Firstly, the FAHP model is established, and stress, deformation, and temperature are selected as evaluation factors. The safety thresholds of stress and deformation are determined by combining the industry specifications and the historical statistical patterns of the massive SHM data. The temperature field of the bridge is simulated and analyzed by combining ANSYS, HYPERMESH, and TAITHREM, and the most unfavorable temperature gradient is determined as a threshold for the safety evaluation. Finally, the scores of indexes of the bridge are determined based on the measured SHM data, which in turn provides a quantitative description of the safety state. The results show that the thresholds determined by the joint industry specifications and the massive SHM data are reasonable; the temperature field simulation model established in this article is consistent with the measured results, and can accurately determine the temperature gradient of the bridge. The safety evaluation result from the FAHP model is the same as the field test results, which verifies the effectiveness and applicability of the proposed method to actual bridge projects.

Geological Hazard Susceptibility Analysis and Developmental Characteristics Based on Slope Unit, Using the Xinxian County, Henan Province as an Example.

Geological hazards in Xinxian County, Xinyang City, Henan Province, are characterized by their small scale, wide distribution, and significant influence from regional tectonics. This study focuses on collapses and landslide hazards within the area, selecting twelve evaluation factors: aspect, slope shape, normalized difference vegetation index (NDVI), topographic relief, distance from geological structure, slope, distance from roads, land use cover type, area of land change (2012-2022), average annual rainfall (2012-2022), and river network density. Utilizing data from historical disaster sites across the region, the information quantity method and hierarchical analysis method are employed to ascertain the information quantity and weight of each factor. Subsequently, a random forest model is applied to perform susceptibility zoning of geological hazards in Xinxian County and to examine the characteristics of these geological disasters. The results show that in the study area, the primary factors influencing the development of geohazards are the distance from roads, rock groups, and distance from geological structure areas. A comparison of the susceptibility results obtained through two methods, the analytic hierarchy process information quantity method and the random forests model, reveals that the former exhibits a higher accuracy. This model categorizes the geohazard susceptibility in the study area into four levels: low, medium, high, and very high. Notably, the areas of very high and high susceptibility together cover 559.17 km2, constituting 35.99% of the study area's total area, and encompass 57 disaster sites, which represent 72.15% of all disaster sites. Geological hazards in Xinxian County frequently manifest on steep canyon inclines, along the curved and concave banks of mountain rivers, within watershed regions, on gully inclines, atop steep cliffs, and on artificially created slopes, among other sites. Areas with very high and high vulnerability to these hazards are mainly concentrated near the county's geological formations. The gneiss formations are widely exposed in Xinxian County, and the gneisses' strength is significantly changed under weathering, which makes the properties of the different degrees of weathering of the rock and soil bodies play a decisive role in the stability of the slopes. This paper provides a basis for evaluating and preventing geologic hazards in the Dabie mountainous area of the South Henan Province, and the spatial planning of the national territory.

Identifying quality indicators for home care services: a modified Delphi and Analytic Hierarchy Process study.

BACKGROUND: As the recipients of home care services, patients have the most direct and profound experience of service quality. There is limited knowledge as to quality indicators for home care services from patients' perspective. This study aimed to identify quality indicators for home care services based on the Service Quality model and determine the weights of these indicators. METHODS: A two-round Delphi survey and Analytic Hierarchy Process consultation were conducted to gather opinions from national experts on quality indicators for home care services developed on the basis of the Service Quality model. Consensus was defined as at least 80% agreement on the importance (important and very important) of indicators among experts. The Analytic Hierarchy Process was used to calculate the weight coefficients of the identified indicators. RESULTS: The response rate was 95.0% and 97.4% in the first and second round, respectively. After two rounds, five first-level (tangibility, reliability, responsiveness, assurance and empathy) and 23 second-level indicators were identified. The Kendall's W values were 0.54 and 0.40 for the first-level and second-level indicators (p < 0.001). The weight coefficients for the first-level and second-level indicators were 0.110-0.298 and 0.019-0.088, respectively. CONCLUSION: Quality indicators for home care services were identified based on the Service Quality model. These indicators can be used to evaluate the service quality of home care from patients' perspective and facilitate to determine work priorities and improve the quality of home care.

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.

Assessing forest fire dynamics and risk zones in Central Indian forests: a comparative study of the Khandwa and North Betul forest divisions of Madhya Pradesh.

Forest fires pose significant environmental and socioeconomic threats, particularly in regions such as Central India, where forest ecosystems are vital for biodiversity and local livelihoods. Understanding forest fire dynamics and identifying fire risk zones are crucial for effective mitigation. The current study explores the spatiotemporal dynamics of forest fires in the Khandwa and North Betul forest divisions in the Central Indian region over 22 years using Mann-Kendall and Sen's slope tests on MODIS (Moderate Resolution Imaging Spectroradiometer) fire point data. We found a nonsignificant increase in forest fires in both divisions. Khandwa showed a nonsignificant slope rise of more than three events per year, while North Betul revealed an increase of around one event per year. The lack of statistical significance suggests that upward trends of forest fire events may result from random fluctuations rather than consistent patterns. Spatial autocorrelation analysis revealed significant clustering of fire incidents in both regions. Khandwa confirmed moderate clustering (Moran's I = 0.043), whereas North Betul showed robust clustering (Moran's I = 0.096). Kernel density estimation further identified high-risk clusters in both divisions, necessitating zonal-wise targeted fire management strategies. Fire risk zonation was developed using the analytic hierarchy process (AHP), combining 10 environmental and socioeconomic factors. The AHP model, validated using MODIS fire data, showed reliable accuracy. The results revealed many of both divisions in the high- to very high-risk categories. Approximately, 45% of the area of the Khandwa and nearly 50% of the area of North Betul fall under high to very high fire risk zones. Khandwa's high-risk areas mainly lie in the northern and southeastern parts, while North Betul lies in the northwestern and north-eastern regions. The identified fire-prone areas indicate the pressing need for local or region-specific fire prevention and mitigation strategies. Thus, the findings of this study provide valuable insights into forest fire risk management and contribute to more focused research and methodological developments.

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.

Optimization and Evaluation of Tourism Mascot Design Based on Analytic Hierarchy Process-Entropy Weight Method.

With the tourism industry continuing to boom, the importance of tourism mascots in promoting and publicizing tourism destinations is becoming increasingly prominent. Three core dimensions, market trend, appearance design, and audience feedback, are numerically investigated for deeply iterating tourism mascot design. Further, a subjective and objective evaluation weighting model based on the hierarchical analysis method (AHP) and entropy weighting method is proposed, aiming to utilize the advantages of these methods and ensure the entireness and correctness of results. Taking the mascots of six famous tourist attractions in Xi'an as an example, the feasibility and effectiveness of the evaluation model are verified. Data analysis and modeling results confirm that the three core evaluation indexes of scalability, innovation, and recommendation should be focused on in the design of tourism mascots in the three dimensions of market trends, appearance design, and audience feedback. The evaluation index scores are 0.1235, 0.1170, and 0.1123, respectively, which further illustrates the priority of mascot design. The evaluation model constructed by the research provides decision-makers with a comprehensive evaluation tool from the perspective of tourist experience, and also effectively assists the optimization process of mascot design. In addition, the model has good versatility and adaptability in structural design and evaluation logic and can be widely used in the optimization and evaluation research of brand mascots.

Bilateral Matching Method for Business Resources Based on Synergy Effects and Incomplete Data.

On the third-party cloud platform, to help enterprises accurately obtain high-quality and valuable business resources from the massive information resources, a bilateral matching method for business resources, based on synergy effects and incomplete data, is proposed. The method first utilizes a k-nearest neighbor imputation algorithm, based on comprehensive similarity, to fill in missing values. Then, it constructs a satisfaction evaluation index system for business resource suppliers and demanders, and the weights of the satisfaction evaluation indices are determined, based on the fuzzy analytic hierarchy process (FAHP) and the entropy weighting method (EWM). On this basis, a bilateral matching model is constructed with the objectives of maximizing the satisfaction of both the supplier and the demander, as well as achieving the synergy effect. Finally, the model is solved using the linear weighting method to obtain the most satisfactory business resources for both supply and demand. The effectiveness of the method is verified through a practical application and comparative experiments.

[Application of Delphi method and analytic hierarchy process to construct the evaluation index system of healthy enterprises].

Objective: Explore the application of Delphi method and analytic hierarchy process to explore the construction of scientific, objective and comprehensive evaluation index system for healthy enterprise construction and promote the construction of healthy enterprises. Methods: In October 2022, through Delphi expert consultation and analytic hierarchy process, the indexes were screened and the weights of the indexes were determined, and the evaluation index system of healthy enterprises was established. Results: The positive coefficients of experts in the two rounds were all 100.00%, the authority coefficient of experts was 0.82, the coefficients of variation of the indexes in the two rounds were all less than 0.30. The coordination coefficients of experts in the first and second rounds were 0.64 and 0.77, respectively (P<0.001) . After two rounds of Delphi method expert consultation, a healthy enterprise evaluation index system including 4 first-level indexes, 14 second-level indexes, and 63 third-level indexes was constructed. Conclusion: The constructed health enterprise evaluation index system is highly scientific and reliable, covering the main factors of healthy enterprise construction, and providing a reliable and quantifiable basis and self-assessment basis for the establishment of healthy enterprises.

[Hierarchical fuzzy comprehensive evaluation of prevention and control level of occupational hazards in coal mines].

Objective: To establish an evaluation model for occupational hazard prevention and control levels in coal mines, to explore the combination of Analytic Hierarchy Process (AHP) and fuzzy comprehensive evaluation, to evaluate the overall situation of occupational hazard prevention and control in coal mines. Methods: In November 2021, Collect information of occupational hazards and their prevention and control status in 30 coal mines. AHP model was first constructed for the elements of occupational hazard prevention and control in coal mines. Then, the AHP and fuzzy comprehensive evaluation method was applied to comprehensively evaluate and grade the occupational hazard prevention and control in coal mines, using the principles of maximum membership and weighted average. Results: The hierarchical fuzzy comprehensive evaluation results for typical coal mine were basically consistent with its occupational hazard prevention and control situation. The dust prevention and control situation was good, the noise prevention and control situation is average, the occupational health monitoring situation was good, the occupational health management situation was average, and the overall level of occupational hazard prevention and control was good. Conclusion: The hierarchical fuzzy comprehensive evaluation model for occupational hazard prevention and control levels, combined with the principles of maximum membership and weighted average, can objectively evaluate and reflect the overall situation of occupational hazard prevention and control in coal mines.

A study on the quality evaluation index system of smart home care for older adults in the community --based on Delphi and AHP.

BACKGROUND: In the context of the "silver wave" and "technology wave", smart home care for older adults in the community provide new ways for China and other countries to support ageing in place. Yet, only very few studies have focused on developing a quality index system of smart care. This study attempted to draw on the SERVQUAL model to establish a quality evaluation index system for smart senior care for older adults in the community. METHODS: On the basis of the service quality model, this paper has integrated qualitative and quantitative analyses using the Delphi and Analytic Hierarchy Process (AHP) methods to construct the index system of smart home care in the community and obtain the weights. These were based on literature research and field interviews in Guangzhou and Shenzhen pilot districts. RESULTS: A quality evaluation indexes system of smart home care for older adults in the community was developed, with 5 primary indices and 33 secondary indices. The weights of the 5 stair indices from high to low were smart emergency assistance 0.332, smart meal assistance 0.272, smart medical assistance 0.229, smart cleaning assistance 0.110 and smart amusement assistance 0.057. CONCLUSION: The results from the weight allocation revealed smart emergency assistance, smart meal assistance, and smart medical care assistance were the most important and crucial aspects of community-based smart home care. The study also suggested that "timeliness", "reliability", and "ease of use" should be given more attention. It is recommended to use this index system as a regulatory benchmark to guide the government bodies, senior care enterprises and communities to take measures to enhance the quality.

Development of a multicriteria decision-making model for evaluating hybrid offspring in the sweetpotato (Ipomoea batatas L.) breeding process.

Sweetpotato variety breeding is always a long process. Screening of hybrid offspring is dominated by empirical judgment in this process. Data analysis and decision fatigue have been troubling breeders. In recent years, the low-efficiency screening mode has been unable to meet the requirements of sweetpotato germplasm innovation. Therefore, it is necessary to construct a high-efficiency method that can screen germplasms for different usages, for mining elite genotypes, and to create dedicated sweetpotato varieties. In this article, the multicriteria decision-making (MCDM) model was constructed based on six agronomic traits, including fresh root yield, vine length, vine diameter, branch number, root number and the spatial distribution of storage roots, and five quality traits, including dry matter content, marketable root yield, uniformity of roots, starch content and the edible quality score. Among these, the edible quality score was calculated by using fuzzy comprehensive evaluation to integrate the sensory scores of color, odor, sweetness, stickiness and fibrous taste. The MCDM model was compared with the traditional screening method via an evaluation in 25 sweetpotato materials. The interference of subjective factors on the evaluation results was significantly reduced. The MCDM model is more overall, more accurate and faster than the traditional screening method in the selection of elite sweetpotato materials. It could be programmed to serve the breeders in combination with the traditional screening method.

AODV-EOCW: An Energy-Optimized Combined Weighting AODV Protocol for Mobile Ad Hoc Networks.

The Ad Hoc On-demand Distance Vector (AODV) is a routing protocol for mobile ad hoc networks (MANETs) and other wireless ad hoc networks. The vanilla AODV protocol is simple and easy to implement because it only uses the hop count as a routing metric. Single-metric route determination also causes problems, such as network congestion and energy exhaustion, which limit the usage of AODV in resource-limited applications. To solve these problems, the authors propose a new routing protocol that combines the analytic hierarchy process (AHP), the entropy weight method (EWM), and AODV. The proposed protocol uses energy, congestion, and the hop count as metrics and weights these three metrics using AHP and EWM. To address the importance of energy in applications, such as drones, the proposed protocol chooses different comparison matrices for AHP at different node residual energy levels. Finally, the node chooses the best route link according to the score (sum of weighted metrics). It is also suitable for wireless sensor networks because the proposed protocol considers the residual energy of the node. The simulation results show that the improved routing protocol can effectively reduce the average end-to-end delay and energy consumption and prolong the lifetime of the whole network.

Multi-Objective Path Optimization in Fog Architectures Using the Particle Swarm Optimization Approach.

IoT systems can successfully employ wireless sensor networks (WSNs) for data gathering and fog/edge computing for processing collected data and providing services. The proximity of edge devices to sensors improves latency, whereas cloud assets provide higher computational power when needed. Fog networks include various heterogeneous fog nodes and end-devices, some of which are mobile, such as vehicles, smartwatches, and cell phones, while others are static, such as traffic cameras. Therefore, some nodes in the fog network can be randomly organized, forming a self-organizing ad hoc structure. Moreover, fog nodes can have different resource constraints, such as energy, security, computational power, and latency. Therefore, two major problems arise in fog networks: ensuring optimal service (application) placement and determining the optimal path between the user end-device and the fog node that provides the services. Both problems require a simple and lightweight method that can rapidly identify a good solution using the constrained resources available in the fog nodes. In this paper, a novel two-stage multi-objective path optimization method is proposed that optimizes the data routing path between the end-device and fog node(s). A particle swarm optimization (PSO) method is used to determine the Pareto Frontier of alternative data paths, and then the analytical hierarchy process (AHP) is used to choose the best path alternative according to the application-specific preference matrix. The results show that the proposed method works with a wide range of objective functions that can be easily expanded. Moreover, the proposed method provides a whole set of alternative solutions and evaluates each of them, allowing us to choose the second- or third-best alternative if the first one is not suitable for some reason.

Content-Based Medical Image Retrieval System for Skin Melanoma Diagnosis Based on Optimized Pair-Wise Comparison Approach.

Medical image analysis for perfect diagnosis of disease has become a very challenging task. Due to improper diagnosis, required medical treatment may be skipped. Proper diagnosis is needed as suspected lesions could be missed by the physician's eye. Hence, this problem can be settled up by better means with the investigation of similar case studies present in the healthcare database. In this context, this paper substantiates an assistive system that would help dermatologists for accurate identification of 23 different kinds of melanoma. For this, 2300 dermoscopic images were used to train the skin-melanoma similar image search system. The proposed system uses feature extraction by assigning dynamic weights to the low-level features based on the individual characteristics of the searched images. Optimal weights are obtained by the newly proposed optimized pair-wise comparison (OPWC) approach. The uniqueness of the proposed approach is that it provides the dynamic weights to the features of the searched image instead of applying static weights. The proposed approach is supported by analytic hierarchy process (AHP) and meta-heuristic optimization algorithms such as particle swarm optimization (PSO), JAYA, genetic algorithm (GA), and gray wolf optimization (GWO). The proposed approach has been tested with images of 23 classes of melanoma and achieved significant precision and recall. Thus, this approach of skin melanoma image search can be used as an expert assistive system to help dermatologists/physicians for accurate identification of different types of melanomas.