A Quality Evaluation System for Dissertation Based on Fuzzy Analytic Hierarchy Process

A dissertation is a research report or scientific paper written by an author to obtain a certain degree. It reflects postgraduates’ research achievements and the educational quality of an institute, even a country. To construct an optimized quality evaluation system for postgraduate dissertation (QESPD), we summarized the influencing factors and invited 10 experienced specialists to rate and prioritize them based on fuzzy analytic hierarchy process. Four primary indicators (innovation, integrity, scientificity and normativity) and 16 sub-indicators were selected to form the evaluation system. The order of primary indicators by weight, was innovation (0.4269), scientificity (0.2807), integrity (0.1728) and normativity (0.1196). The top five sub-dimensions were theoretical originality, scientific value, data reliability, design rationality and evidence credibility. To demonstrate the effectiveness of the proposed system, a case study was performed. In the case study, it was demonstrated that the established two-index-hierarchy QESPD in this study was a more scientific and reasonable evaluation system worthy of promotion and application.

NOVEL INTEGRABLE HAMILTONIAN HIERARCHIES WITH SIX POTENTIALS

This paper aims to construct six-component integrable hierarchies from a kind of matrix spectral problems within the zero curvature formulation.Their Hamiltonian formulations are furnished by the trace identity,which guarantee the commuting property of infinitely many symmetries and conserved Hamiltonian functionals.Illustrative examples of the resulting integrable equations of second and third orders are explicitly computed.

Integrating Levels of Hierarchical Organization in Porous Organic Molecular Materials

Porous organic molecular materials(POMMs)are an emergent class of molecular-based materials characterized by the formation of extended porous frameworks,mainly held by non-covalent interactions.POMMs represent a variety of chemical families,such as hydrogen-bonded organic frameworks,porous organic salts,porous organic cages,C-H···πmicroporous crystals,supramolecular organic frameworks,π-organic frameworks,halogen-bonded organic framework,and intrinsically porous molecular materials.In some porous materials such as zeolites and metal organic frameworks,the integration of multiscale has been adopted to build materials with multifunctionality and optimized properties.Therefore,considering the significant role of hierarchy in porous materials and the growing importance of POMMs in the realm of synthetic porous materials,we consider it appropriate to dedicate for the first time a critical review covering both topics.Herein,we will provide a summary of literature examples showcasing hierarchical POMMs,with a focus on their main synthetic approaches,applications,and the advantages brought forth by introducing hierarchy.

The suitability assessment on site selection for bottom seeding scallop culture based on analytic hierarchy process

Scallop culture is an important way of bottom-seeding marine ranching,which is of great significance to improve the current situation of fishery resources.However,there are some problems in site-selection evaluation of marine ranching,such as imperfect criteria system,complex structure,untargeted criteria quantification,etc.In addition,no site-selection evaluation method of bottom-seeding culture areas for scallops is available.Therefore,we established a hierarchy structure model according to the analytic hierarchy process(AHP)theory,in which social,physical,chemical,and biological environments are used as main criteria,and marine functional zonation,water depth,current,water temperature,salinity,substrate type,water quality,sediment quality,red tide,phytoplankton,and zooplankton are used as sub-criteria,on which a multi-parameter evaluation system is set up.Meanwhile,the dualism method,assignment method,and membership function method were used to quantify sub-criteria,and a quantitative evaluation for the entire criteria was added,including the evaluation and analysis of two types of unsuitable environmental situations.By overall consideration in scallop yield,quality,and marine ranching construction objectives,the weight of the main criteria could be determined.Five grades in the suitability corresponding to the evaluation result were divided,and the Python language was used to create an evaluation system for efficient calculation and intuitive presentation of the evaluation outcome.Eight marine cases were simulated based on existing survey data,and the results prove that the method is feasible for evaluating and analyzing the site selection of bottom-seeding culture areas for scallops under various environmental situations.The proposed evaluation method can be promoted for the site selection of bottom-seeding marine ranching.This study provided theoretical and methodological references for the site selection evaluation of other types of marine ranching.

FROM WAVE FUNCTIONS TO TAU-FUNCTIONS FOR THE VOLTERRA LATTICE HIERARCHY

For an arbitrary solution to the Volterra lattice hierarchy,the logarithmic derivatives of the tau-function of the solution can be computed by the matrix-resolvent method.In this paper,we define a pair of wave functions of the solution and use them to give an expression of the matrix resolvent;based on this we obtain a new formula for the k-point functions for the Volterra lattice hierarchy in terms of wave functions.As an application,we give an explicit formula of k-point functions for the even GUE(Gaussian Unitary Ensemble)correlators.

Iterative physical optics method based on efficient occlusion judgment with bounding volume hierarchy technology

This paper builds a binary tree for the target based on the bounding volume hierarchy technology,thereby achieving strict acceleration of the shadow judgment process and reducing the computational complexity from the original O(N^(3))to O(N^(2)logN).Numerical results show that the proposed method is more efficient than the traditional method.It is verified in multiple examples that the proposed method can complete the convergence of the current.Moreover,the proposed method avoids the error of judging the lit-shadow relationship based on the normal vector,which is beneficial to current iteration and convergence.Compared with the brute force method,the current method can improve the simulation efficiency by 2 orders of magnitude.The proposed method is more suitable for scattering problems in electrically large cavities and complex scenarios.

An Evidence-Based CoCoSo Framework with Double Hierarchy Linguistic Data for Viable Selection of Hydrogen Storage Methods

Hydrogen is the new age alternative energy source to combat energy demand and climate change.Storage of hydrogen is vital for a nation’s growth.Works of literature provide different methods for storing the produced hydrogen,and the rational selection of a viable method is crucial for promoting sustainability and green practices.Typically,hydrogen storage is associated with diverse sustainable and circular economy(SCE)criteria.As a result,the authors consider the situation a multi-criteria decision-making(MCDM)problem.Studies infer that previous models for hydrogen storage method(HSM)selection(i)do not consider preferences in the natural language form;(ii)weights of experts are not methodically determined;(iii)hesitation of experts during criteria weight assessment is not effectively explored;and(iv)three-stage solution of a suitable selection of HSM is unexplored.Driven by these gaps,in this paper,authors put forward a new integrated framework,which considers double hierarchy linguistic information for rating,criteria importance through inter-criteria correlation(CRITIC)for expert weight calculation,evidence-based Bayesian method for criteria weight estimation,and combined compromise solution(CoCoSo)for ranking HSMs.The applicability of the developed framework is testified by using a case example of HSM selection in India.Sensitivity and comparative analysis reveal the merits and limitations of the developed framework.

GIS-Based Multi-Criteria Decision Analysis (MCDA) and Analytical Hierarchy Process (AHP) Techniques to Derive Flood Risks Management on Rice Productivity in Gishari Marshland

Floods are phenomenon with significant socio-economic implications mainly for human loss, agriculture, livestock, soil loss and land degradation, for which many researchers try to identify the most appropriate methodologies by analyzing their temporal and spatial development. This study therefore attempts to employ the GIS-based multi-criteria decision analysis and analytical hierarchy process techniques to derive the flood risks management on rice productivity in the Gishari Agricultural Marshland in Rwamagana district, Rwanda. Here, six influencing potential factors to flooding, including river slope, soil texture, Land Use Land Cover through Land Sat 8, rainfall, river distance and Digital Elevation Model are considered for the delineation of flood risk zones. Data acquisition like Landsat 8 images, DEM, land use land cover, slope, and soil class in the study area were considered. Results showed that if the DEM is outdated or inaccurate due to changes in the terrain, such as construction, excavation, or erosion, the predicted flood patterns might not reflect the actual water flow. This could result unexpected flood extents and depths, potentially inundating rice fields that were not previously at risk and this, expectedly explained that the increase 1 m in elevation would reduce the rice productivity by 0.17% due to unplanned flood risks in marshland. It was found that the change in rainfall distribution in Gishari agricultural marshland would also decrease the rice productivity by 0.0018%, which is a sign that rainfall is a major factor of flooding in rice scheme. Rainfall distribution plays a crucial role in flooding analysis and can directly impact rice productivity. Oppositely, another causal factor was Land Use Land Cover (LULC), where the Multivariate Logistic Regression Model Analysis findings showed that the increase of one unit in Land Use Land Cover would increase rice productivity by 0.17% of the total rice productivity from the Gishari Agricultural Marshland. Based on findings from these techniques, the Gishari Agricultural Marshlands having steeped land with grassland is classified into five classes of flooding namely very low, low, moderate, high, and very high which include 430%, 361%, 292%, 223%, and 154%. Government of Rwanda and other implementing agencies and major key actors have to contribute on soil and water conservation strategies to reduce the runoff and soil erosion as major contributors of flooding.

An Eight Component Integrable Hamiltonian Hierarchy from a Reduced Seventh-Order Matrix Spectral Problem

We present an eight component integrable Hamiltonian hierarchy, based on a reduced seventh order matrix spectral problem, with the aim of aiding the study and classification of multicomponent integrable models and their underlying mathematical structures. The zero-curvature formulation is the tool to construct a recursion operator from the spatial matrix problem. The second and third set of integrable equations present integrable nonlinear Schrödinger and modified Korteweg-de Vries type equations, respectively. The trace identity is used to construct Hamiltonian structures, and the first three Hamiltonian functionals so generated are computed.

Research on Detection of Food additives Based on Terahertz Spectroscopy and Analytic Hierarchy Process

Terahertz time-domain spectroscopy is a kind of far-infrared spectroscopy technology,and its spectrum reflects the internal properties of substances with rich physical and chemical information,so the use of terahertz waves can be used to qualitatively identify food additives containing nitrogen elements.Analytic hierarchy process(AHP)was originally used to solve evaluation-type problems,and this paper introduces it into the field of terahertz spectral qualitative analysis,proposes a terahertz time-domain spectral qualitative identification method combined with analytic hierarchy process,and verifies the feasibility of the method by taking four common food additives(xylitol,L-alanine,sorbic acid,and benzoic acid)and two illegal additives(melamine,and Sudan Red No.I)as the objects of study.Firstly,the collected terahertz time-domain spectral data were pre-processed and transformed into a data set consisting of peaks,peak positions,peak numbers and overall trends;then,the data were divided into comparison and test sets,and a qualitative additive identification model incorporating analytic hierarchy process was constructed and parameter optimisation was performed.The results showed that the qualitative identification accuracies of additives based on single factors,i.e.,overall trend,peak value,peak position,and peak number,were 80.23%,70.93%,67.44%,and 40.70%,respectively,whereas the identification accuracy of the analytic hierarchy process qualitative identification method based on multi-factors could be improved to 92.44%.In addition,the fuzzy characterisation of the absorption spectrum data was binarised in the data pre-processing stage and used as the base data for the overall trend,and the recognition accuracy was improved to 94.19%by combining the fuzzy characterisation method of such data with the hierarchical analysis qualitative recognition model.The results show that it is feasible to use terahertz technology to identify different varieties of additives,and this paper constructs a hierarchical analytical qualitative model with better effect,which provides a new means for food additives detection,and the method is simple in steps,with a small demand for samples,which is suitable for the rapid detection of small samples.

Analytic Hierarchy Process for Technological Risks in the Process of Innovative Drug Development in China

Objective To identify the critical risks in the process of innovative drug research and development,and to provide reference for improving the efficiency of innovative drug development and risk control in China.Methods Expert investigation and analytic hierarchy process were used to determine the weights of different risks.Results and Conclusion The research and analysis results showed that the risks at different stages of development had different effects on the success rate of drug development,among which the risk at the drug discovery stage influenced the most.In the drug discovery stage,inappropriate target selection had the greatest impact on the success rate of drug development.The lack of appropriate cell tissue or animal models had the greatest impact on the success rate of drug development from the discovery of a compound to the application for clinical trials.The difference in changes between nonclinical and clinical studies had the greatest impact on the success rate of drug development from early clinical studies to pivotal clinical studies.Incorrect dose selection had the greatest impact on the success rate of drug development from pivotal clinical studies to marketing authorization applications.The biggest impact from the marketing authorization application to the approval stage was inadequate communication with regulators.After investigating the weight of risk factors in the process of innovative drug development based on scientific methods,a new perspective for the risk control of new drug development and improving the research and development efficiency is provided.

Delineating Groundwater Potential Zones Using Geospatial and Analytical Hierarchy Process Techniques in the Upper Omo-Gibe Basin,Ethiopia

In regions with unpredictable rainfall and limited water supply,it’s crucial to pinpoint areas with high potential for groundwater and find the best spots for groundwater resource development.This study utilizes the Analytic Hierarchy Process(AHP)in combination with Geographic Information Systems(GIS)to evaluate the potential groundwater zones in the Gombora watershed within the Omo Gibe basin in Ethiopia.Combining these two tools provided a detailed map showing potential groundwater areas.These zones are determined based on various thematic maps containing information about geology,soil texture,lineament density,slope,land use,and drainage density.The AHP method combines these data layers by assigning weights to each layer based on its importance for groundwater recharge.These weighted layers are then overlaid using a GIS platform to produce a conclusive map of potential groundwater areas.The groundwater potential within the watershed was qualitatively divided into five categories with area coverages of very good(1.6%),good(7.4%),moderate(21.4%),poor(51.6%),and very poor(17.9%)of thewatershed area.The accuracy of the groundwater potential zones was evaluated using the receiver operating characteristic(ROC)curve and the area under the curve(AUC),producing good results(AUC=75.5%).This research has shown that integrating AHP with GIS can effectively pinpoint potential groundwater zones.Additionally,the findings could play a key role in determining suitable locations for new groundwater wells and supplying valuable insights to decision-makers to aid in planning and implementing sustainable strategies for managing groundwater resources in the watershed.

过犹不及:金字塔层级对地方国有企业创新的非线性影响研究

增强国有企业创新力是进一步做强做优做大国有资本和国有企业的关键。本文从资源动态演进的视角,考察了金字塔股权架构对地方国有企业创新的非线性影响,并探寻促进地方国有企业创新的有效途径。研究发现,地方国有企业金字塔层级与创新产出之间呈现显著的倒U型关系,且金字塔层级位于3~4层时最有利于地方国有企业创新。进一步地,这一倒U型关系的形成机制为资源释放和资源侵蚀在金字塔层级叠加过程中的动态演进:当金字塔层级较少时,市场化改革的资源释放效应提高了企业的创新产出;当金字塔层级较多时,代理问题导致的资源侵蚀效应降低了企业的创新意愿,呈现“过犹不及”的态势。本文证实了地方国有企业金字塔层级对创新的非线性影响,丰富了地方国有企业金字塔股权架构经济后果的研究,对地方国有企业治理模式选择和创新能力提升具有重要启示。

人工智能风险体系与模块化评价指标构建实证研究

[研究目的]在人工智能蓬勃发展的时代,开展人工智能风险体系构建及其对应的模块化评价指标研究,以全面反映AI发展所带来的潜在风险,为不同领域的研究者提供决策依据。[研究方法]首先,基于扎根理论和专家调查法,系统地抽取和设计模块化人工智能风险评价指标;其次,采用层次分析法,对各指标权重进行测算,形成量化后的得分表,并对风险等级进行划分;最后,借助问卷调查法和专家调查法,对该体系进行应用实证研究,以验证其科学性及可行性。[研究结果/结论]人工智能风险体系包含由9个一级指标和41个二级指标组成的模块化评价指标。该体系涵盖技术、伦理、法律和社会等多个维度。基于此体系可以针对某一人工智能事件或功能,使用主观评价的方法对每一个风险子项进行打分,并最终得出总分。模块化指标可以灵活拆分,以量化测度不同领域的AI风险,兼顾全维度与具象维度的AI风险测度问题。

静脉用药调配中心感染防控质量评价指标体系的构建

目的:构建静脉用药调配中心(静配中心)感染防控质量评价指标体系。方法:在河南省静配中心感染防控现状调查结果和文献回顾基础上,基于“结构-过程-结果”理论模型,采用专家咨询法和层次分析法,制订静配中心感染防控质量评价指标体系。结果:两轮专家咨询权威系数分别为0.89和0.90,肯德尔协调系数分别为0.358和0.531(P均<0.05)。构建的指标体系包括3个一级指标、7个二级指标、21个三级指标。三级指标中调配操作规范性、环境卫生学监测合格率、工作人员手卫生监测合格率和质量控制管理规范性组合权重最高,分别为0.086、0.070、0.070和0.063。结论:构建的指标体系专业、科学和全面,对静配中心感染防控规范化管理具有指导意义。

基于层次分析法的废弃铁路沿线景观再生及更新策略研究--以兰阿铁路城区段为例

城市铁路作为一种工业文化景观,是城市文化在空间中的物理表征,深刻地影响着城市空间肌理。但是,随着城市更新的发展,城市由增量建设向存量提质转变,大量废弃铁路成为城市中常见的存量空间,并且具有一定的再生潜力和价值。因此,科学评价废弃铁路文化资源是其合理规划与利用的前提。文章以兰阿铁路城区段为例,采用层次分析法,从交通再生价值、生态再生价值、商旅再生价值三个目标层以及12个评价指标构建城市废弃铁路沿线景观再生评价体系,并根据评价结果,提出相应的再生策略,以期对城市废弃铁路沿线景观再生提供科学依据。

马斯洛需要层次论的手术室精准护理对卵巢癌手术患者负性情绪及手术配合度的影响

目的:探究基于马斯洛需要层次论的手术室精准护理对卵巢癌手术患者负性情绪及手术配合度的影响。方法:采用随机数字表法将某院自2021年10月至2023年10月收治的98例行手术治疗的卵巢癌患者分为观察组和对照组,各49例。对照组接受卵巢癌手术室常规护理干预,观察组接受手术室精准护理应用马斯洛需要层次论护理干预,比较两组手术一般情况、负性情绪、手术配合度及护理满意度。结果:观察组术后出血量、术后排气时间、术后尿管留置时间显著短于对照组(t=3.511,2.383,3.155;P<0.05),两组手术时间比较无显著性差异(P>0.05);干预后,观察组焦虑量表、特质焦虑量表评分显著低于对照组(t=4.674,4.410;P<0.001),观察组手术配合度显著高于对照组(χ^(2)=4.653,P<0.05),观察组护理满意度总分显著高于对照组(t=2.808,P<0.01)。结论:手术室精准护理应用马斯洛需要层次论干预卵巢癌手术患者能改善患者的负性情绪,提高手术配合度和护理满意度,促进术后康复。

Multi-agent Based Hierarchy Simulation Models of Carrier-based Aircraft Catapult Launch

With the aid of multi-agent based modeling approach to complex systems, the hierarchy simulation models of carrier-based aircraft catapult launch are developed. Ocean, carrier, aircraft, and atmosphere are treated as aggregation agents, the detailed components like catapult, landing gears, and disturbances are considered as meta-agents, which belong to their aggregation agent. Thus, the model with two layers is formed i.e. the aggregation agent layer and the meta-agent layer. The information communication among all agents is described. The meta-agents within one aggregation agent communicate with each other directly by information sharing, but the meta-agents, which belong to different aggregation agents exchange their information through the aggregation layer first, and then perceive it from the sharing environment, that is the aggregation agent. Thus, not only the hierarchy model is built, but also the environment perceived by each agent is specified. Meanwhile, the problem of balancing the independency of agent and the resource consumption brought by real-time communication within multi-agent system （MAS） is resolved. Each agent involved in carrier-based aircraft catapult launch is depicted, with considering the interaction within disturbed atmospheric environment and multiple motion bodies including carrier, aircraft, and landing gears. The models of reactive agents among them are derived based on tensors, and the perceived messages and inner frameworks of each agent are characterized. Finally, some results of a simulation instance are given. The simulation and modeling of dynamic system based on multi-agent system is of benefit to express physical concepts and logical hierarchy clearly and precisely. The system model can easily draw in kinds of other agents to achieve a precise simulation of more complex system. This modeling technique makes the complex integral dynamic equations of multibodies decompose into parallel operations of single agent, and it is convenient to expand, maintain, and reuse the program codes.

新疆石河子垦区150团农田防护林生态状况评价

干旱沙区的农田防护林是人工绿洲的重要生态屏障,在防治风沙灾害、改善区域小气候、保障人民正常生产生活等方面发挥着至关重要的作用。为了解垦区农田防护林生态状况,以新疆石河子垦区150团为研究区域,构建了基于遥感生态和林学两个层面的评价指标体系,使用Landsat 8 OLI遥感数据提取了农田防护林遥感生态指标,并采用层析分析法对该地区的农田防护林生态状况进行等级划分和制图。同时,考虑了农田防护林的布局和实际树种情况,对150团的农田防护林生态状况进行了分析。结果表明:150团的农田防护林生态状况中等,其中生态状况表现为优的林带占总林带的21.2%,生态状况表现为中等的林带占41.8%,生态状况表现为低的占30.9%,而生态状况较差的占6.1%;防护林布局基本合理,连接度和环度分别为0.4307和0.1444,林带走向合格率为61.6%。在南北方向,林网状况存在差异;防护林树种较少且搭配不合理。

基于模糊层次分析法的重庆传统木构民居建筑安全评价研究——以龙兴古镇刘家大院为例

重庆地区传统木构民居类型多样,探索适用于重庆地区传统木构民居的安全评价方法,对于重庆以及国内其他地区木构传统民居的保护与维修具有重要意义。在分析重庆地区地域特色和民居建筑特性的基础上,结合模糊层次分析法(Fuzzy Analytic Hierarchy Process,FAHP),建立适用于重庆地区的传统木构民居安全评价方法,该方法包括21项风险指标,涵盖自然灾害风险、建筑本体质量灾害风险和人为灾害风险,全面考虑了威胁民居安全的风险因素,并能够反映风险因素的权重差异。将该评价方法应用于重庆龙兴古镇刘家大院的检测和评价中,评价结果与实际情况相符,证明该方法准确可行;评价结果能够显示不同指标的风险大小,有利于提出针对性的保护与修缮建议。