Hierarchical Evaluation Model Research Articles

Hierarchical Models of Information Systems Security Metrics: A Comparative Sectoral Approach

Information system security metrics are critical in assessing and mitigating data protection risks. Executives must improve the security of their information systems. However, it is important to note that there is a wide variety of metrics available and that generic measurements may not be effective for the broader enterprise. This article provides an overview of information system security metrics and introduces a novel hierarchical model for them. Adopting a comparative approach across five sectors (health, finance, industry, government, and education), the Analytical Hierarchy Process (AHP) was used to design and evaluate the model in each sector context. The objective was to identify the variation in security criteria based on the sector. The results obtained confirm that the criteria weights vary according to the sector involving a change in the hierarchical evaluation model.

Research on Evaluation System of Medical Imaging Equipment Dynamic Acquisition Technology Based on Multiple Criteria Decision Analysis

To construct an evaluation model system for dynamic data acquisition methods of medical imaging equipment in hospitals. The analytic hierarchy process (AHP) of the multiple criteria decision analysis method is used to study the model. Through multi-criteria decision analysis, the evaluation index system of dynamic data acquisition technology of medical imaging equipment is constructed from aspects such as the reliability and traceability of data acquisition, the interactivity of the acquisition mode, and the extensibility of application analysis. A hierarchical evaluation model of dynamic acquisition technology for medical imaging equipment is constructed, which includes 5 primary indexes, 14 secondary indexes, and 38 tertiary indexes. We have constructed a qualitative and quantitative evaluation index for the dynamic acquisition technology of medical imaging equipment. The weight of the quantitative index "reliability" is 30%, and the weights of the qualitative indexes "security", "traceability", "interactivity", and "scalability" are 25%, 20%, 15%, and 10% respectively. It can be used to study the methods and technical characteristics of three kinds of dynamic data acquisition of medical equipment and form a technical evaluation scheme for dynamic data acquisition.

Research on Risk and Value Assessment under Extreme Conditions Based on Analytic Hierarchy Process and Delphi Method

With global climate change worsening, the property insurance sector faces growing challenges from increasingly severe extreme weather events. This paper pinpoints four key factors influencing insurance decision-making: disaster frequency, damage severity, consumer price index, and population dynamics. Analyzing data from ten countries, including China and the U.S., from 2014 to 2023, we establish a hierarchical evaluation model to assess these factors' correlations. Results show risk magnitudes of 0.925 for the U.S. and 0.982 for China, suggesting potential opportunities for insurance underwriting amid extreme weather. Using hierarchical analysis and the Delphi method, we assign weights to factors, identifying buildings scoring above three points as valuable and those with environmental indicator scores below 1.5 as needing protection. This approach aids in evaluating building value and protection requirements, assisting insurers in crafting informed risk management strategies.

Assessing E-Commerce Service Quality: A Hierarchical Evaluation Model for Online Sales Firms

Assessing E-Commerce Service Quality: A Hierarchical Evaluation Model for Online Sales Firms

Research on Partner Selection in Enterprise Innovation Ecosystem

In the face of fierce market competition, enterprises must ensure the competitiveness of their products or services through technological innovation. However, the complexity of technology often surpasses the capabilities of individual enterprises, leading them to deepen cooperation with other organizations. The entities within the enterprise innovation ecosystem depend on each other, collaborate closely, and rely on core enterprises to integrate resources, thereby creating system value and enhancing competitiveness. The purpose of this paper is to explore the process of selecting appropriate ecosystem partners. It begins by providing an overview of relevant concepts, characteristics, selection factors, and methods. Subsequently, it analyzes the roles, resources, and synergy evolution of the entities within the ecosystem. An evaluation system encompassing operation, core, synergy, and development capability is then established. This system comprises 16 indicators, including organization scale and reputation, and is accompanied by a hierarchical evaluation model. Finally, the validity of the evaluation system is confirmed through empirical analysis, utilizing the Analytic Hierarchy Process (AHP) and the fuzzy comprehensive evaluation method.

The Path of “Dual-Teacher” Teacher Cultivation in Applied Local Higher Teacher Colleges under the Background of Big Data

Abstract The cultivation path of the applied “dual-teacher” teacher team in this paper mainly relies on the qualification standard and evaluation system. Big data technology is used to collect data, deeply mine fragmented data, and further extract index factors that affect the quality of teachers. The multi-level fuzzy hierarchical evaluation model realizes the quantification of the decision-making process with less quantitative information, and determines the weights through the multi-level comparison of importance, to test and evaluate the teaching ability of “dual-teacher” teachers. The results show that, among the 166 survey respondents, 77 respondents belong to the “ Dual-teacher” teachers, accounting for about 45.03%. The primary needs and ways for most of the teachers to participate in the training of “dual-teacher” teachers are to improve the practical ability of industry and enterprise positions (score 0.86) and the school-based training of dual-teacher teachers (0.93), which is centralized in the college. In evaluating “dual-teacher” teaching, the weight of industry-teaching integration is 0.3378, so the ability of industry-teaching integration is a more meaningful indicator. College students are satisfied with “dual-teacher teaching”, and the score shows that the essential satisfaction is more than half of the total number of samples, which is 343.

Construction of a prognostic hierarchical model for patients with HER2 positive breast cancer with brain metastases.

e13030 Background: Brain metastasis occurs in about 50% of advanced HER2-positive breast cancer patients. In clinical practice, we need accurate model to predict the patients’ survival time. According to survival time, we can arrange reasonable treatment strategy for HER2 positive breast cancer with brain metastases. Methods: The study recruited HER2-positive breast cancer brain metastasis (BCBM) patients who attended the Fifth Medical Center of PLA General Hospital from June 2003 to June 2022.All statistics were performed using SPSS version 22.0 and R version 3.4.3 software. Results: This study included 300 patients with HER2-positive BCBM. The median age at Brain Metastases diagnosis was 48.5 years, and the median Brain Metastases Overall Survival time (BMOS) was 18.0 months (95% CI: 14.6-21.4). A single-factor analysis of BMOS revealed that age, number of brain metastasis lesions, number of extracranial lesions during BCBM, radiotherapy after BCBM, anti-HER2 therapy after BCBM, and survival prognosis after BCBM were associated with survival prognosis after diagnosis of BCBM. According to a multi-factor analysis, the age, the number of brain metastases, radiotherapy after BCBM, and anti-HER2 therapy after BCBM were all independent factors influencing survival after diagnosis of BCBM. Different independent prognostic factors comprised the patient hierarchical evaluation model. Patients' warning scores range from 0 to 7. We divided the patients into three groups with obvious differences in prognosis： Low- intermediate-risk (score≥1), stroke group (score≥3) and high-risk group (score≥6). The patient prognosis was worse when the warning score was high. The results of Kaplan-Meier survival curve analysis showed significant prognosis differences between the three groups of patients (P < 0.0001). The mean Area Under Curve of the receiver operating characteristic curve for 1-yeasr, 2-year, and 3-year prognosis prediction was 0.69,0.71, and 0.67, respectively. For low-risk patients, the prognosis was significantly improved by using any anti-HER2 medications (P<0.05). Trastuzumab + Pertuzumab can significantly improve the prognosis of patients at intermediate risk (P<0.001, HR=0.24,95%CI: 0.13-0.43). Patients in the intermediate-risk group received both anti-HER2 medication and combined radiotherapy significantly prolonged BMOS in patients who received only drug therapy or radiotherapy (P=0.0132). Conclusions: A survival and prognostic stratification model was constructed based on the clinicopathological characteristics and treatment pattern of a large cohort of HER2-positive breast cancer patients with brain metastases, and the patients were divided into the low-risk group, intermediate-risk group and high-risk group. The optimal individualized treatment strategy was recommended according to different groups.

A General Construction Method of Virtual Simulation Experiment Platform Based on Bibliometrics and Analytic Hierarchy Process

Virtual simulation can solve the challenges of high cost, long cycle time, and inaccessibility in traditional experimental teaching, which is far-reaching for talent training. This study combines bibliometric visualization theory with AHP (Analytic Hierarchy Process). It establishes a hierarchical evaluation model of a virtual simulation experimental teaching platform based on 842 questionnaires and 4787 articles, including 68,306 citation records, and deconstructing the complex evaluation problem into several multidimensional factors by attributes and relationships. Based on this, a virtual simulation experimental teaching platform construction scheme for IP protocol analysis based on a network covert communication perspective is outputted, which is compatible with the research results. The experimental platform takes a task-driven teaching method as the core, mainly including four modules of context creation, task determination, independent learning, and effect evaluation. The experience of building this platform can be extended to other disciplines, leading the teaching reform exploration of practice-based, innovation-focused, and engineering-critical, helping to implement the flipped classroom, and promoting the development of education modernization.

Comprehensive Evaluation of Pavement Waterproofing Layer Materials for Bridge and Tunnel Projects

In order to achieve the preferential selection of pavement waterproofing layer materials, so that the waterproofing layer material selection is more scientific and objective, eliminating the impact of subjective factors, this paper uses hierarchical analysis to build a hierarchical evaluation model of pavement waterproofing layer. Based on the literature review method, a two-tier evaluation index of the layered evaluation model of pavement waterproofing layer materials was constructed, mainly three first-tier indexes of performance assessment, service life assessment, and cost assessment, under which the second-tier indexes of waterproofing performance, durability, weather resistance, impermeability, crack resistance, thermal stability, aging resistance, low temperature crack resistance, fatigue resistance, material cost, construction cost, and maintenance cost were established. And through the hierarchical analysis method of calculation, test the consistency by deriving the weight of each indicator, where the most important first layer of indicators for performance, the weight of 0.5390, the second layer of indicators is more important for waterproof performance (0.5303), thermal stability (0.3550), low-temperature crack resistance (0.3550), material cost (0.6333). The study provides a scientific and objective evaluation model for the preferential selection of pavement waterproofing layer materials.

Research on Evaluation of Eco-Metro Station Levels Based on Hierarchical Analysis Models

With the help of hierarchical analysis and fuzzy comprehensive evaluation theory, this paper innovatively constructs a hierarchical evaluation model of underground metro station ecological building projects from six aspects, namely, land saving, material saving, indoor environment, water saving, energy saving and operation management, and combines with the premise of spatial specificity and complexity of underground metro stations, so as to provide a theoretical basis for the development of ecological buildings in the construction of underground metro stations. The article selects the ecological building of underground station in Qingdao, China to carry out comprehensive evaluation and validation. The results of the study show that the evaluation model based on hierarchical analysis can effectively quantify the ecological grades of metro station projects.

A Hierarchical Model for Quality Evaluation of Mixed Source Software Based on ISO/IEC 25010

With the emergence of mixed source software, the existing quality models are not able to better assess the community quality and autonomy controllability of mixed source software. To fill this gap, we propose a hierarchical model in this paper for quality assessment of mixed source software. In our model, the new attributes are proposed to meet the quality requirements of mixed source software based on the ISO/IEC 25010 standards, and a set of metrics are designed for the new attributes. The model evaluates the quality of mixed source software through quality attributes that have been quantified by the metrics. Applying our quality model to some mixed source software and comparing the model results with the actual situation, we verify whether our proposed two quality attributes, community intensity and autonomy controllability, can effectively assess the quality of mixed source software. The results of the experiments show that our model is indeed effective in assessing the quality of mixed source software. An important feature of our model is that the model has good flexibility, and the set of quality attributes and metrics can be adjusted freely, which provides a flexible and feasible way for various software quality assessment requirements.

Materials selection of 3D printed polyamide-based composites at different strain rates: A case study of automobile front bumpers

The selection of 3D printed composite materials considering multiple criteria has become a challenging issue for designers/engineers and can be regarded as a typical decision-making problem. Especially for diverse engineering applications, the different strain rates encountered need to be addressed in the decision-making process. In this study, a systematic hierarchical evaluation model of 3D printed polyamide-based composites with 27 indicators is established considering economic, environmental, social and mechanical aspects. The mechanical responses at four strain rates (8 × 10−4 s−1, 8 × 10−3 s−1, 1700 s−1 and 3510 s−1) are incorporated into the model. A hybrid decision-making approach combining the fuzzy DEMATEL (Decision Making Trial and Evaluation Laboratory)-Entropy and fuzzy TODIM (Tomada de Decisão Interativa Multicritério)-VIKOR (VlseKriterijumska Optimizacija I Kompromisno Resenje) methods is proposed to solve the composite material selection problem. An automobile front bumper, as an empirical application, is investigated to demonstrate the proposed model and decision-making approach. The results show that PACF-C, that is the short carbon fibre reinforced polyamide printed with a concentric strategy, is the optimal alternative. This study provides an effective approach for solving the material selection problem of 3D printed composites.

Fuzzy Comprehensive Evaluation of APTS Dispatcher Working Level Based on Cloud Model

Many cities in China have built an advanced public transportation system (APTS) in recent years. These systems cannot carry out automated dispatches but rely on the dispatcher to ensure normal operations. Based on the theory of fuzzy comprehensive evaluation, this study created a hierarchical evaluation model to evaluate the work level of the dispatcher. Firstly, a hierarchical evaluation system was established based on the data of line complexity and dispatch workload provided by the APTS. Secondly, we assigned the weight of the evaluating indicator by combing an expert scoring method and the entropy weight method. We then transformed the quantitative data into qualitative evaluation data with a cloud model. Through a comparison with the standard cloud, the work level of an APTS dispatcher can be defined. The evaluation results for 12 cities in China showed that there was no obvious connection between the working level and bus company size, but the work level was always higher in large cities. We finally obtained the standard range of the evaluation indicator through cluster analysis. This method can be used as a reference to evaluate the work level of dispatchers in other cities, and can reflect the correlation between the work level and dispatching system construction, population and city size.

Optimization of English Classroom Quality Evaluation Model with AHP

This work takes English classroom quality as the research object. Improving the quality of English classrooms is not only an unavoidable requirement for the current curriculum reform’s deepening and development, but also a necessary development trend of the evaluation system reform, and the call of the majority of classroom teaching position. The country invested financial, labor, and material resources, and students have also invested a lot of study time, but the English classroom effect is not satisfactory. The main issue is a lack of adequate evaluation of the teaching process as well as a scientific, fair, and practical technique for assessing classroom quality. This work combines AHP and BP networks to propose a method (AHP-IGA-BP) for evaluating the quality of English classrooms. The content of this work is as follows: (1) A hierarchical model and index system for English classroom quality evaluation based on AHP are constructed. Through the process of constructing a judgment matrix, single-level ranking, consistency check, and total-level ranking, the complete English classroom quality evaluation index weight is finally obtained, which realizes the transformation of subjective information into data with specific weight. (2) combine the original data with the aforementioned index weight data produced using AHP, as well as the neural network’s learning and training samples. Build a BP network structure to effectively evaluate the quality of English classrooms. (3) The BP network is optimized based on the improved GA algorithm.

Smart Urban Mobility System Evaluation Model Adaptation to Vilnius, Montreal and Weimar Cities

To date, there is no developed and validated way to assess urban smartness. When evaluating smart city mobility systems, different authors distinguish different indicators. After analysing the evaluation indicators of the transport system presented in the scientific articles, the most relevant and influential indicators were selected. This article develops a hierarchical evaluation model for evaluating a smart city transportation system. The indicators are divided into five groups called “factors”. Several indicators are assigned to each of the listed groups. A hybrid multi-criteria decision-making (MCDM) method was used to calculate the significance of the selected indicators and to compare urban mobility systems. The applied multi-criteria evaluation methods were simple additive weighting (SAW), complex proportional assessment (COPRAS), and technique for order preference by similiarity to ideal solution (TOPSIS). The significance of factors and indicators was determined by expert evaluation methods: the analytic hierarchy process (AHP), direct, when experts evaluate the criteria as a percentage (sum of evaluations of all criteria 100%) and ranking (prioritisation). The evaluation and comparison of mobility systems were performed in two stages: when the multi-criteria evaluation is performed according to the indicators of each factor separately and when performing a comprehensive assessment of the smart mobility system according to the integrated significance of the indicators. A leading city is identified and ranked according to the smartness level. The aim of this article is to create a hierarchical evaluation model of the smart mobility systems, to compare the smartness level of Vilnius, Montreal, and Weimar mobility systems, and to create a ranking.

Residual coal distribution in China and adaptability evaluation of its resource conditions to underground coal gasification

This paper researched the distribution and the characteristics of residual coal resources for their adaptability into underground coal gasification (UCG) technology to promote a potential green technology for the development of residual coal resources in China. The results reflected that the average recovery rate of resources for coal mines was only 37.67% in China, and the residual coal reserves reached 148.53 gigatons (Gt), of which 52.51% occurred in North China. Furthermore, these resources are mainly distributed in the buried depth shallower than 800 m, accounting for 87.15%. And residual coal types were primarily bituminite with a percentage of 72.89%. We established a multi-level model with membership functions that included an analytic hierarchy and a fuzzy comprehensive evaluation with variable weight theory. As a result, a varying weight fuzzy hierarchical evaluation model for the resource conditions feasibility of residual coal with UCG technology was established. Finally, the model was applied to the resource condition feasibility evaluation of UCG industrial tests at Zhongliangshan, Huating, and Shanjiaoshu Mines. The industrial tests showed that the evaluation model constructed in this paper could comprehensively, objectively, and intuitively reflect the adaptability of residual coal resources to UCG technology, providing a scientific reference for UCG project decision-making.

The Construction of English Smart Classroom and the Innovation of Teaching Mode under the Background of Internet of Things Multimedia Communication

There are some problems in English smart classroom, such as slow response speed of related platforms and room for improvement of teaching effect. Therefore, it is necessary to construct English smart classroom and innovate teaching mode under the background of Internet of Things (IoT) multimedia communication. The teaching objectives are divided into classroom teaching objectives, curriculum objectives, and education and training objectives, so as to design the technical support for English smart classroom, that is, to build a smart classroom integrating cloud application platform (including students’ learning cloud and teachers’ teaching cloud), teaching platform, resource platform, learning space, and interactive classroom by using Internet of Things multimedia communication technology, and build an innovative teaching mode of English wisdom classroom. The fuzzy hierarchical evaluation model is used to design the fuzzy hierarchical evaluation algorithm. Through the fuzzy hierarchical evaluation algorithm, the teaching effect of smart classroom is evaluated, and the final evaluation result is obtained. The results show that the average platform login time of the proposed method is always below 0.3 s, the average score of the summative evaluation is high, the evaluation time is always below 0.4 s, the average communication delay is 0.54 s, and the user satisfaction is always above 9.2. The practical application effect is better.

Fuzzy Comprehensive Hierarchical Evaluation Model for Lightning Disaster in Oil Storage Depots

An oil storage depot is one of the most dangerous places in the petrochemical industry. Lightning strikes present a significant risk to the regular operation of oil storage depots and the safety of the staff. This paper established a lightning disaster risk model using practical evaluation techniques to provide insight into the lightning disaster prevention methods used in oil storage depots both domestically and abroad. The risk assessment of lightning disaster in oil storage depots was performed according to this model, after which the risk index factors were classified. Furthermore, this paper reasonably resolved the problems surrounding the limited use of lightning protection standards and the challenge in quantifying the qualitative factors during lightning disaster risk assessment in oil storage depots. This references the risk assessment of lightning disaster in oil storage depots and the related lightning protection design.

State Evaluation of SF6 high Voltage Circuit Breaker based on improved Radar Chart and Catastrophe Progression Method

The comprehensive on-line assessment of power equipment health status was an important research content of power production and maintenance.According to the operation characteristics of SF6 high voltage circuit breaker, the hierarchical evaluation model of high voltage circuit breaker was established, and the subjective and objective weights were fitted and optimized by multiplication synthesizer; the improved radar chart method was applied to the importance evaluation of circuit breaker index; the final evaluation result of circuit breaker was obtained according to the catastrophe progression method, which made the evaluation process more intuitive and concise, and avoided the subjectivity. A practical example showed that the proposed model could objectively and effectively evaluate the state of high voltage circuit breaker.Compared with the traditional radar chart method, the improved radar chart method combined with the catastrophe series method solved the problems of information sharing and non-unique evaluation results among the indicators in the traditional radar chart method, which made the evaluation results more accurate and reasonable.

Research on human performance evaluation model based on neural network and data mining algorithm

In order to effectively evaluate personnel performance, a distributed data mining algorithm for spatial networks based on BP neural wireless network is proposed. In the cloud computing environment, an excavator is used to construct multiple input multiple output spatial network data, analyze the data structure, and perform redundant data compression of massive data through time-frequency feature extraction. Combined with the adaptive matching filtering method, the characteristics of the data are matched. The spatial frequency feature extraction method is used to locate the features of the multiple-input multiple-output spatial network data. In order to improve the accuracy of data mining, the BP neural network is used to classify and identify the extracted data features to achieve the optimization of data mining. A wireless sensor network is a wireless network composed of a large number of stationary or moving sensors in a self-organizing and multi-hop manner. It cooperatively senses, collects, processes, and transmits the information of the perceived objects in the geographical area covered by the network and finally puts these The information is sent to the owner of the network. This algorithm improves the accuracy of personnel performance evaluation, simultaneously establishes a hierarchical analysis and quantitative evaluation model for the performance of government managers, and adjusts the results of hierarchical statistical analysis on government administrators as needed. The performance evaluation and optimization of government administrators were introduced. The empirical analysis results show that the method has higher accuracy for government managers’ performance evaluation, higher efficiency of big data processing, and better integration.