Projection pursuit cluster model and its application in water quality assessment

One of the difficulties frequently encountered in water quality assessment is that there are many factors and they cannot be assessed according to one factor, all the effect factors associated with water quality must be used. In order to overcome this issues the projection pursuit principle is introduced into water quality assessment, and projection pursuit cluster(PPC) model is developed in this study. The PPC model makes the transition from high dimension to one-dimension. In other words, based on the PPC model, multifactor problem can be converted to one factor problem. The application of PPC model can be divided into four parts: (1) to estimate projection index function Q(); (2) to find the right projection direction ; (3) to calculate projection characteristic value of the i th sample z-i, and (4) to draw comprehensive analysis on the basis of z-i. On the other hand, the empirical formula of cutoff radius R is developed, which is benefit for the model to be used in practice. Finally, a case study of water quality assessment is proposed in this paper. The results showed that the PPC model is reasonable, and it is more objective and less subjective in water quality assessment. It is a new method for multivariate problem comprehensive analysis.

Dynamic Assessment on Regional Eco-environmental Quality Using AHP-Statistics Model—A Case Study of Chaohu Lake Basin

An indicator system closely connected with eco-environment, in which indicator involves in such fields as society, economy, resources, environment and ecology, is first proposed for eco-environmental quality assessment. Then, a hierarchical model with four levels is established by virtue of these indicators and attributes. In the model, weights of indicators and attributes are determined by combining Delphi method with the Analytic Hierarchy Process (AHP) and a statistic method is used to eliminate the influences arising from the differences in dimension and magnitude of indicators. On these grounds, an AHP-statistics model is provided for regional eco-environmental quality assessment. As a case, such AHP-statistics model is utilized in the dynamic analysis of regional eco-environmental assessment in Chaohu Lake basin. Study results show that natural environmental quality in the watershed was in the declining state while social environmental quality was in a markedly improved situation from 1996, and the synthetic eco-environmental quality was gradually and slowly improved under the common influences of both natural and social environmental factors. Example of application testified the capacities of above methodology to evaluate the real and dynamic state of regional eco-environmental quality.

Comprehensive Assessment of Seawater Quality Based on an Improved Attribute Recognition Model

The attribute recognition model (ARM) has been widely used to make comprehensive assessment in many engineering fields, such as environment, ecology, and economy. However, large numbers of experiments indicate that the value of weight vector has no relativity to its initial value but depends on the data of Quality Standard and actual samples. In the present study, the ARM is enhanced with the technique of data driving, which means some more groups of data from the Quality Standard are selected with the uniform random method to make the calculation of weight values more rational and more scientific. This improved attribute recognition model (IARM) is applied to a real case of assessment on seawater quality. The given example shows that the IARM has the merits of being simple in principle, easy to operate, and capable of producing objective results, and is therefore of use in evaluation problems in marine environment science.

Multi-agent Blind Model and Its Application to Regional Eco-environmental Quality Assessment

Through denoting each expert as an agent and viewing a multiple criteria decision-making as a synthesis problem of aggregating experts＇ ratings, a multi-agent blind model （MABM） is developed for regional eco-environmental quality assessment. In this model, the ratings of the evaluated object under an index, given by expert group, are first utilized to construct a series of blind numbers. In general, each index will correspond to different blind numbers. On the basis of aggregating index weights, the rank score in the form of a blind number is obtained for the evaluated object. Then, by means of calculating expected value of the above blind number, its rank score is further converted into a crisp value. By way of comparing the expected value with classification standards, eco-environmental quality of the evaluated sample could he identified successfully in the end. As a case, the MABM is used to evaluate the eco-environmental quality of Chaohu Lake basin. Study result shows that the MABM is a useful model for regional eco-environmental quality assessment.

Perceptual Quality Assessment of Omnidirectional Images:Subjective Experiment and Objective Model Evaluation

Virtual reality(VR) environment can provide immersive experience to viewers.Under the VR environment, providing a good quality of experience is extremely important.Therefore, in this paper, we present an image quality assessment(IQA) study on omnidirectional images. We first build an omnidirectional IQA(OIQA) database, including 16 source images with their corresponding 320 distorted images. We add four commonly encountered distortions. These distortions are JPEG compression, JPEG2000 compression, Gaussian blur, and Gaussian noise. Then we conduct a subjective quality evaluation study in the VR environment based on the OIQA database. Considering that visual attention is more important in VR environment, head and eye movement data are also tracked and collected during the quality rating experiments. The 16 raw and their corresponding distorted images,subjective quality assessment scores, and the head-orientation data and eye-gaze data together constitute the OIQA database. Based on the OIQA database, we test some state-of-the-art full-reference IQA(FR-IQA) measures on equirectangular format or cubic formatomnidirectional images. The results show that applying FR-IQA metrics on cubic format omnidirectional images could improve their performance. The performance of some FR-IQA metrics combining the saliency weight of three different types are also tested based on our database. Some new phenomena different from traditional IQA are observed.

Human-Centric Composite-Quality Modeling and Assessment for Virtual Desktop Clouds

There are several motivations, such as mobility, cost, and secu- rity, that are behind the trend of traditional desktop users transi- tioning to thin-client-based virtual desktop clouds （VDCs）. Such a trend has led to the rising importance of human-centric performance modeling and assessment within user communities that are increasingly making use of desktop virtualization. In this paper, we present a novel reference architecture and its eas- ily deployable implementation for modeling and assessing objec- tive user quality of experience （QoE） in VDCs. This architec- ture eliminates the need for expensive, time-consuming subjec- tive testing and incorporates finite-state machine representa- tions for user workload generation. It also incorporates slow-mo- tion benchmarking with deep-packet inspection of application task performance affected by QoS variations. In this way, a ＂composite-quality＂ metric model of user QoE can be derived. We show how this metric can be customized to a particular user group profile with different application sets and can be used to a） identify dominant performance indicators and troubleshoot bottlenecks and b） obtain both absolute and relative objective user QoE measurements needed for pertinent selection of thin-client encoding configurations in VDCs. We validate our composite-quality modeling and assessment methodology by us- ing subjective and objective user QoE measurements in a re- al-world VDC called VDPilot, which uses RDP and PCoIP thin-client protocols. In our case study, actual users are pres- ent in virtual classrooms within a regional federated university system.

A Novel Two-Layer Model for Overall Quality Assessment of Multichannel Audio

With the development of multichannel audio systems, corresponding audio quality assessment techniques, especially the objective prediction models, have received increasing attention. Existing methods, such as PEAQ(Perceptual Evaluation of Audio Quality) recommended by ITU, usually lead to poor results when assessing multichannel audio, which have little correlation with subjective scores. In this paper, a novel two-layer model based on Multiple Linear Regression(MLR) and Neural Network(NN) is proposed. Through the first layer, two indicators of multichannel audio, Audio Quality Score(AQS) and Spatial Perception Score(SPS) are derived, and through the second layer the overall score is output. The final results show that this model can not only improve the correlation with the subjective test score by 30.7% and decrease the Root Mean Square Error(RMSE) by 44.6%, but also add two new indicators: AQS and SPS, which can help reflect the multichannel audio quality more clearly.

Urban Air Quality Plans and Integrated Assessment Methodologies

The air quality directive （2008/50/EC （of the European Parliament and of the Council of 21 May 2008）） requires European Member States to design appropriate AQPs （air quality plans） for zones and agglomerations where the air quality does not comply with the limit values and to assess possible emission reduction measures to decrease concentration levels. The Portuguese agglomeration of Porto Litoral is one of the several European Union urban areas that had to develop and implement AQPs to reduce particulate matter （PM10）. The AQPs were initially designed based on a scenario approach and using an air quality model, which was applied over the study region for the reference situation with the current PM10 emissions, and for a reduction scenario with PM10 emissions re-estimated considering the implementation of abatement measures. Aiming to cost-efficiently optimize Porto Litoral PM10 abatement measures, the assessment procedure was repeated using an optimization approach based on the RIAT ＋ （regional integrated assessment tool ＋）. Porto Litoral urban area＇s technical and non-technical measures were characterized （including associated costs） and, through the application of the air quality model to 20 emissions abatement scenarios, S-R （source-receptor） relationships were created. This paper comparatively describes the air quality plans designed to improve PM10 levels in the Porto Litoral agglomeration based on both the scenario analysis and the optimization approach.

Application of machine learning models in groundwater quality assessment and prediction:progress and challenges

Groundwater quality assessment and prediction(GQAP)is vital for protecting groundwater resources.Traditional GQAP methods can not adequately capture the complex relationships among attributes and have the disadvantage of being computationally demanding.Recently,the application of machine learning(ML)in GAQP(GQAPxML)has been widely studied due to ML’s reliability and efficiency.While many GQAPxML publications exist,a thorough review is missing.This review provides a comprehensive summary of the development of ML applications in the field of GQAP.First,the workflow of ML modeling is briefly introduced,as are data preparation,model development,model evaluation,and model application.Second,299 publications related to the topic are filtered,mainly through ML modeling.Subsequently,many aspects of GQAPxML,such as publication trends,the spatial distribution of study areas,the size of data sets,and ML algorithms,are discussed from a bibliometric perspective.In addition,we review in detail the well-established applications and recent findings for several subtopics,including groundwater quality assessment,groundwater quality modeling using groundwater quality parameters,groundwater quality spatial mapping,probability estimation of exceeding the groundwater quality threshold,groundwater quality temporal prediction,and the hybrid use of ML and physics-based models.Finally,the development of GQAPxML is explored from three perspectives:data collection and preprocessing,model building and evaluation,and the broadening of model applications.This review provides a reference for environmental scientists to better understand GQAPxML and promotes the development of innovative methods and improvements in modeling quality.

Can ChatGPT evaluate research quality?

Purpose:Assess whether ChatGPT 4.0 is accurate enough to perform research evaluations on journal articles to automate this time-consuming task.Design/methodology/approach:Test the extent to which ChatGPT-4 can assess the quality of journal articles using a case study of the published scoring guidelines of the UK Research Excellence Framework(REF)2021 to create a research evaluation ChatGPT.This was applied to 51 of my own articles and compared against my own quality judgements.Findings:ChatGPT-4 can produce plausible document summaries and quality evaluation rationales that match the REF criteria.Its overall scores have weak correlations with my self-evaluation scores of the same documents(averaging r=0.281 over 15 iterations,with 8 being statistically significantly different from 0).In contrast,the average scores from the 15 iterations produced a statistically significant positive correlation of 0.509.Thus,averaging scores from multiple ChatGPT-4 rounds seems more effective than individual scores.The positive correlation may be due to ChatGPT being able to extract the author’s significance,rigour,and originality claims from inside each paper.If my weakest articles are removed,then the correlation with average scores(r=0.200)falls below statistical significance,suggesting that ChatGPT struggles to make fine-grained evaluations.Research limitations:The data is self-evaluations of a convenience sample of articles from one academic in one field.Practical implications:Overall,ChatGPT does not yet seem to be accurate enough to be trusted for any formal or informal research quality evaluation tasks.Research evaluators,including journal editors,should therefore take steps to control its use.Originality/value:This is the first published attempt at post-publication expert review accuracy testing for ChatGPT.

Assessing seawater quality with a variable fuzzy recognition model

With the rapid development of the marine economy industry, human exploitation of marine resources is increasing, which is contributing to the growing trend of eutrophication and frequent occurrence of red tide. Accordingly, investigations of seawater quality have attracted a great deal of attention. This study was conducted to construct a seawater environmental quality assessment model based on the variable fuzzy recognition model. The uncertainty and ambiguity of the seawater quality assessment were then considered, combining the monitoring values of evaluation indicators with the standard values of seawater quality. Laizhou Bay was subsequently selected for a case study. In this study, the correct variable model for different parameters was obtained according to the linear and nonlinear features of evaluation objects. Application of the variable fuzzy recognition model for Laizhou Bay, water quality evaluation and comparison with performance obtained using other approaches revealed that the generated model is more reliable than traditional methods, can more reasonably determine the water quality of various samples, and is more suitable for evaluation of a multi-index, multi-level, nonlinear marine environment system; accordingly, the generated model will be an effective tool for seawater quality evaluation.

Maternal and Child Health Care Quality Assessment: An Improved Approach Using K-Means Clustering

High maternal and child deaths in developing countries are frequently linked to poor health services provided to pregnant women and children. To improve the quality of maternal, neonatal and child health (MNCH) services, the government and other stakeholders in MNCH emphasize the importance of quality assessment. However, effective quality assessment approaches are mostly lacking in most developing countries, particularly in Tanzania. This study, therefore, aimed at developing a quality assessment approach that can effectively assess and report on the quality of MNCH services. Due to the need for a good quality assessment approach that suits a resource-constrained environment, machine learning-based approach was proposed and developed. K-means algorithm was used to develop a clustering model that groups MNCH data and performs cluster summarization to discover the knowledge portrayed in each group on the quality of MNCH services. Results confirmed the clustering model’s ability to assign the data points into appropriate clusters;cluster analysis with the collaboration of MNCH experts successfully discovered insights on the quality of services portrayed by each group.

Benefits, Difficulties, and Success Factors of Three Different Quality Assessment Processes in Estonia

Quality assessment systems for business organisations and also for vocational schools were established in Estonia at the beginning of 2000s. Almost ten years later, corresponding systems were introduced also for higher education institutions （HEIs）. All these assessment systems are based on the European Foundation of Quality Management （EFQM） excellence model. The aim of this paper is to analyse benefits, difficulties, and success factors of quality assessment processes in Estonian business organisations, vocational schools, and HEIs. The study is based on the analysis of feedback questionnaire of 404 representatives from participating organisations （HEIs, vocational schools, and business enterprises） and assessors. Our analysis revealed that quality assessment processes including self-assessment reporting had a positive effect on organisation development and it has given the participants certain benefits and new challenges. As a consequence, knowledge about quality management as well as the self-assessment skills has been improved. The main difficulties were connected to limited time resources and with problems to recognize direct benefits of quality assessment. As substantial difficulties, limitations of analytical and report-writing skills were considered. As the biggest success factor, an involvement of managers on different levels decision making was recognized. The analysis revealed that there are a number of similar benefits and difficulties in the quality assessment systems of different organizations.

Evaluation of hydro-chemistry in a phreatic aquifer in the Vindhyan Region, India, using entropy weighted approach and geochemical modelling

Groundwater quality monitoring and geochemical characterization in the phreatic aquifer are critical for ensuring universal and equitable access to clean,reliable,and inexpensive drinking water for all.This research was intended to investigate the hydrogeochemical attributes and mechanisms regulating the chemistry of groundwater as well as to assess spatial variation in groundwater quality in Satna district,India.To accomplish this,the groundwater data comprising 13 physio-chemical parameters from thirty-eight phreatic aquifer locations were analysed for May 2020 by combining entropy-weighted water quality index(EWQI),multivariate statistics,geochemical modelling,and geographical information system.The findings revealed that the groundwater is fresh and slightly alkaline.Hardness was a significant concern as 57.89% of samples were beyond the permissible limit of the World Health Organisation.The dominance of ions were in the order of Ca^(2+)> Na^(+)> Mg^(2+)> K^(+) and HCO_(3)^(-)> SO_(4)^(2-)> Cl^-> NO_(3)^(-)> F^(-).Higher concentration of these ions is mainly concentrated in the northeast and eastern regions.Pearson correlation analysis and principal component analysis(PCA) demonstrated that both natural and human factors regulate groundwater chemistry in the region.The analysis of Q-mode agglomerative hierarchical clustering highlighted three significant water clusters.Ca-HCO_3 was the most prevalent hydro-chemical facies in all three clusters.Geochemical modelling through various conventional plots indicated that groundwater chemistry in the research region is influenced by the dissolution of calcite/dolomite,reverse ion exchange,and by silicate and halite weathering.EWQI data of the study area disclosed that 73.69% of the samples were appropriate for drinking.Due to high salinity,Magnesium(Mg^(2+)),Nitrate(NO_(3)^(-)),and Bicarbonate(HCO_(3)^(-)) concentrations,the north-central and north-eastern regions are particularly susceptible.The findings of the study may be accomplished by policymakers and groundwater managers to achieve sustainable groundwater development at the regional scale.

Using a Coupled Air Quality Modeling System for the Development of an Air Quality Plan in Madrid (Spain): Source Apportionment and Analysis Evaluation of Mitigation Measures

In this contribution, we use a coupled air quality modelling system (AQM) as a tool to design and develop an air quality plan in Madrid. AQM has allowed us to obtain a preliminary evaluation of the effect of mitigation measures over regional and local air quality levels. To achieve these goals, we have prepared a sophisticated AQM, coupling the meteorological model WRF, the emission model AEMM, and the photochemical model CMAQ. AQM was evaluated using the whole modelling year 2010 working with high horizontal resolution, 3 km for the region of Madrid and 1km for urban metropolitan area of Madrid. Two different analyses have been realized: a source apportionment exercise following a zero-out methodology to obtain the contribution to the air quality levels of the different emission sector;and an evaluation of the main mitigation measures considered in the air quality plan using sensitivity analysis. The air quality plan was focused on the improvement of NO2 levels and AQM analyzed the effect of the mitigation measures during ten episodes of 2011 where NO2 or O3 levels were the highest of the year;so we analyzed the effect of the mitigation plan in worst conditions. Results provided by the AQM system show that it accomplishes the European Directive modelling uncertainty requirements and the mean absolute gross error for 1-h maximum daily NO2 is 31% over locations with higher levels of this atmospheric pollutant;the road traffic is the main contributor to the air quality levels providing a 81% for NO2, 67% for CO and 46% for PM10;measures defined in the plan achieve to reduce up to 11 μgm-3 NO2 levels offering highest reductions over urban areas with traffic influence.

长江中上游重要渔业水域环境质量评估

为准确评估长江中上游重要渔业水域水环境质量现状及变化趋势,提高水质评价效率,本研究基于11个水质参数,采用水质指数法(water quality index,WQI)对2006-2021年长江中上游三个重要渔业水域水质进行了综合评价,建立WQI min综合评价模型。结果显示:(1)长江中上游重要渔业水域的水温和高锰酸盐指数呈上升趋势;基于地表水环境质量标准(GB38338-2002),单因素水质评价结果表明监测水域内整体水质处于地表水Ⅴ类水标准,部分年份达劣Ⅴ类,主要污染指标为总氮。(2)通过综合评价方法分析,长江中上游重要渔业水域整体为“良”;2006~2021年长江中上游重要渔业水域水质质量呈逐年改善的趋势,且上游保护区的改善较大。(3)基于WQI方法,确定了长江中上游重要渔业水域的关键水质参数为:总氮、高锰酸盐指数、汞、溶解氧、氨氮、悬浮物以及水温,分别构建了上游保护区、中华鲟保护区以及四大家鱼保护区的WQI_(min)模型;考虑权重和不考虑权重的WQI min模型对比分析表明,考虑权重的WQI min模型的水质评价结果更加准确,该方法可有效评估长江中上游重要渔业水域的水质变化特征并可扩展用于其他水域。

基于大语言模型的个性化实验报告评语自动生成与应用

在计算机实验报告评阅过程中,不同的实验报告评价体系呈现出多样性和差异性,固化的实验评语模板缺乏个性化的内容,评价结果往往未给出可解释性的依据。针对以上问题,提出基于大语言模型的个性化实验报告评语自动生成框架。通过主题-评估决策-集成提示策略,从教师的实验需求、代码质量需求中抽取该实验特有的评价体系,形成评估决策树,构建计算机软件方向课程共享的评估决策树库。设计基于大语言模型和决策树的实验要求、代码质量主题评级方法,从评估决策树库检索匹配学生实验报告内容的评估决策树,结合实验报告和代码文本,自动生成实验主题、代码质量主题定量或定性的评级结果及对应的可解释性依据。在实验报告模板中融入学生已完成的实验任务、主题评级结果、评价依据等,生成个性化的实验评语。实验结果表明,基于主题-评估决策-集成提示策略的决策树生成结果明显优于未用提示的方法,该策略各部分具有一定的有效性和合理性,同时自动生成的评级结果和教师原先批阅的评阅结果对比,软件测试、面向对象程序设计、电商金融课程示例匹配正确率均达到90%以上。从任课教师对于自动生成的评语评分分析,评语在流畅性、相关性、合理性3个维度上达到了较高的质量水平。

软件产品成熟度模型与评估研究

简述了技术成熟度模型、软件能力成熟度模型(SW-CMM)和测试能力成熟度模型(TMM)等成熟度模型的侧重点和适用范围,分析了产品质量与产品成熟度之间的关系,指出了软件产品成熟度的影响因素与其表征维度的不同点,基于产品自身、质量和应用视角,考虑了产品的完整性、响应性、安稳性和适用性等特性,提出了软件产品成熟度评估模型,并给出了相应的成熟度等级定义及评估方法。

基于组合赋权-云模型的抽蓄电站高质量发展评价体系

为科学评价生产期抽蓄电站高质量发展现状、把握电站发展的薄弱环节、明确建设期及新投运电站发展方向,根据抽蓄电站定位及高质量发展内涵,经过2轮筛选,构建了包含服务电力系统稳定运行、经济、绿色、创新、共享5个一级指标以及18个二级指标的评价指标体系;选用层次分析法–决策实验分析方法确定指标权重,运用云模型评价各电站高质量发展等级。最后,选取A抽蓄电站为算例验证评价体系适用性。评价结果显示,该电站服务电力系统稳定运行、绿色和共享3个指标表现均为良好,经济和创新指标表现为中等,与电站实际运行情况相符合。该验证结果表明,采用上述方法构建的评价指标体系有很好的适用性。

晋升激励、资源错配与经济高质量发展——基于新旧考核模式差异化视角

基于“晋升锦标赛”治理模式的特征事实,使用2003—2016年287个地级及以上城市面板数据,实证考察新旧考核模式下晋升激励对经济高质量发展的差异化影响。结果表明:(1)传统考核观下晋升激励显著阻碍了经济高质量发展,资源错配是晋升激励阻碍经济高质量发展的重要原因。(2)在资源丰富程度较低、政府财政透明度较低、年轻官员主政的城市以及直辖市中,晋升激励对经济高质量发展的负面影响更大;晋升激励对政绩存在“可视性偏差”。(3)新型考核观下晋升激励缓解了资源错配问题,促进了城市经济高质量发展,具有差异化空间溢出的特点。