Research Progress on Evaluation Frameworks of Regional Ecological Sustainability

As natural ecosystems provide the material basis and fundamental support for regional sustainable devel-opment,the sustainability of natural ecosystems is an important prerequisite and a viable approach for the achievement of regional sustainable development.It is also the final criteria to assess whether sustainable development paradigm is successful.Along with the increasing impacts of human activities on natural ecosystems,the evaluation of regional ecological sustainability has become one of the key issues for research on macro ecology and sustainable development.Based on different unit of indicators,this study firstly groups the evaluation frameworks of regional ecological sus-tainability into three major types:comprehensive index evaluation with dimensionless unit,monetary valuation,and biophysical quantity measurement.We then discuss and compare these types in terms of basic principles,scope of ap-plications,advantages and shortcomings.Finally,drawn on the discussion about characteristics of ecological sustain-ability,we outline the current trend and future directions of regional ecological sustainability evaluation,for instance,transition from sustainable development evaluation to sustainability science,integration of goal-oriented and problem-solving approaches,combination of spatial pattern analysis and ecological sustainability evaluation,and en-hancement of ecological sustainability evaluation at landscape scale.

Indicator system and evaluation framework for sustainable development

An indicator system of sustainable development was established and an evaluation framework for sustainable development was drawn in this study.

Drought risk assessment in China:Evaluation framework and influencing factors

Global warming and rapid economic development have led to increased levels of disaster risk in China.Previous attempts at assessing drought risk were highly subjective in terms of assessment methods and selection of the assessment indicators and which resulted in appreciable uncertainty in the results of these risk assessments.Based on the assumption that areas with historically high drought losses are more likely to suffer future high drought losses,we develop a new drought risk assessment model that includes historical drought loss data.With this model,we map the regional differentiation of Chinese drought risk.Regions with high(extreme high)drought risk account for 4.3%of China’s area.Five significant high-risk areas have been identified:Northeast China,North China,the east part of Northwest China,the east part of Southwest China and a small part in the west of Northwest China.Areas with high and extreme high drought risk are dominant in the Heilongjiang Province,accounting for 32%of the total area,followed by the Ningxia Hui Autonomous Region,with 26%of total area.The contribution of each influencing factor has been quantified,which indicates that high-exposure and high-vulnerability account for the high-risk of drought.We recommend that measures like strengthening the protection of cultivated land and reducing dependence on the primary industry should be taken to mitigate to drought-induced losses.

Comprehensive evaluation framework for intervention on health effects of ambient temperature

Despite the existence of many interventions to mitigate or adapt to the health effects of climate change,their effectiveness remains unclear.Here,we introduce the Comprehensive Evaluation Framework for Intervention on Health Effects of Ambient Temperature to evaluate study designs and effects of intervention studies.The framework comprises three types of interventions:proactive,indirect,and direct,and four categories of indicators:classification,methods,scope,and effects.We trialed the framework by an evaluation of existing intervention studies.The evaluation revealed that each intervention has its own applicable characteristics in terms of effectiveness,feasibility,and generalizability scores.We expanded the framework's potential by offering a list of intervention recommendations in different scenarios.Future applications are then explored to establish models of the relationship between study designs and intervention effects,facilitating effective interventions to address the health effects of ambient temperature under climate change.

Energy neutrality potential of wastewater treatment plants:A novel evaluation framework integrating energy efficiency and recovery

Wastewater treatment plants(WWTPs)consume large amounts of energy and emit greenhouse gases to remove pollutants.This study proposes a framework for evaluating the energy neutrality potential(ENP)of WWTPs from an integrated perspective.Operational data of 970 WWTPs in the Yangtze River Economic Belt(YREB)were extracted from the China Urban Drainage Yearbook 2018.The potential chemical and thermal energies were estimated using combined heat and power(CHP)and water source heat pump,respectively.Two key performance indicators(KPIs)were then established:the energy self-sufficiency(ESS)indicator,which reflects the offset degree of energy recovery,and the comprehensive water–energy efficiency(CWEE)indicator,which characterizes the efficiency of water–energy conversion.For the qualitative results,98 WWTPs became the benchmark(i.e.,CWEE=1.000),while 112 WWTPs were fully self-sufficient(i.e.,ESS≥100%).Subsequently,four types of ENP were classified by setting the median values of the two KPIs as the critical value.The WWTPs with high ENP had high net thermal energy values and relatively loose discharge limits.The explanatory factor analysis of water quantity and quality verified the existence of scale economies.Sufficient carbon source and biodegradability condition were also significant factors.As the CWEE indicator was mostly sensitive to the input of CHP,future optimization shall focus on the moisture and organic content of sludge.This study proposes a novel framework for evaluating the ENP of WWTPs.The results can provide guidance for optimizing the energy efficiency and recovery of WWTPs.

An easy-to-use evaluation framework for benchmarking entity recognition and disambiguation systems

Entity recognition and disambiguation （ERD） is a crucial technique for knowledge base population and information extraction. In recent years, numerous papers have been published on this subject, and various ERD systems have been developed. However, there are still some confusions over the ERD field for a fair and complete comparison of these systems. Therefore, it is of emerging interest to develop a unified evaluation framework. In this paper, we present an easy-to-use evaluation framework （EUEF）, which aims at facilitating the evaluation process and giving a fair comparison of ERD systems. EUEF is well designed and released to the public as an open source, and thus could be easily extended with novel ERD systems, datasets, and evaluation metrics. It is easy to discover the advantages and disadvantages of a specific ERD system and its components based on EUEF. We perform a comparison of several popular and publicly available ERD systems by using EUEF, and draw some interesting conclusions after a detailed analysis.

A comprehensive performance evaluation framework of complex products based on a fuzzy AHP and DS theory

With the development of computer technique,performance evaluation of complex products is playing an increasingly critical role in ensuring product quality and improving development process.An extensible comprehensive performance evaluation framework with the integration of effective group decision-making algorithms could be a supporting tool to achieve an efficient evaluation process and reduce comprehensive evaluation dif-ficulty.This paper aims to provide a evaluation framework with friendly interactive operation and extensive expansibility,which adopts a multi-expert evaluation approach based on fuzzy,analytical hierarchy process(FAHP)and Dempstere–Shafer(DS)theory(FADS)in order to consider experts’relative importance degree.In addition,an extensible evaluation process and related auxiliary functions are implemented in the framework,including the establishment of an assessment index system,integration and calls of multiple types of testing data preprocessing methods and index assessment methods suitable for small sample data,graphical result display and data analysis,etc.Finally,performance evaluation cases of two models of airborne radar anti-jamming are presented to verify the feasibility and expansibility of our assessment framework.The group decision-making method shows its effectiveness compared with the experimental evaluation results by the FAHP researched method.

A preliminary study of cryosphere service function and value evaluation

Cryosphere science research and development(R&D) has been strongly committed to public service, integrating natural sciences with socioeconomic impacts. Owing to the current shift from purely natural cryosphere scientific research to linking cryosphere science with socioeconomic and cultural science, cross-disciplinary research in this field is emerging, which advocates future cryosphere science research in this field. Utilizing the cryosphere service function(CSF), this study establishes CSF and its value evaluation system. Cryosphere service valuation can benefit the decisionmakers' and public's awareness of environmental protection. Implementing sustainable CSF utilization strategies and macroeconomic policymaking for global environmental protection will have profound and practical significance as well as avoid environmental degradation while pursuing short-term economic profits and achieving rapid economic development.

Research and comprehensive evaluation on delivery schemes of the Grand Inga hydropower station

Congo River has abundant hydropower resources,and large-scale cascade power stations,such as the Grand Inga,can be constructed in downstream locations.However,the fragile economic foundations of the Democratic Republic of the Congo and neighbor!ng Central African countries,and the small-scale regional power consumption market prohibit the implementation of large-scale hydro power projects.As the high-voltage,I on g-dista nee power transmission tech no logy matures,hydropower from the Grand Inga can be delivered to load centers in other regions of Africa.This study establishes a 6 dime nsional comprehe nsive assessment model using the best-worst method to evaluate large-scale,I on g-distance,cross-border power intercon necti on projects.The model is applied to evaluate all the can didate in ter-regional power delivery schemes of the Inga III hydropower station,and the evaluation results can effectively help investment institutions and policy makers in policy making and potential market targeting.

Concept and evaluation method of equipment system of systems contribution rate

To scientifically evaluate the equipment system of systems(SoS)contribution rate,a contribution rate calculation method based on a structural equation model(SEM)is proposed in this paper.The connotation and evaluation process of the equipment SoS contribution rate were redefined and standardized.To solve the existing problems in the application of the original contribution rate formula,a modified contribution rate calculation formula is proposed.Finally,the contribution rate evaluation index was divided into latent and explicit variables.The measurement and structural equations in the SEM were used to calculate and analyze the latent variables.The simulation results show that the number of defense lines of air defense weapon equipment has a greater impact on the linear configuration than the group configuration.When the number of K-type air defense weapons is sufficient,the two-layer linear configuration should be adopted with 20 air defense weapon systems.When the number of K-type air defense weapons is insufficient,the single-layer group configuration should be adopted with 12 air defense weapon systems.

Designing and evaluating assessment and learning in adaptive learning systems

The recent emergence of adaptive language learning systems calls for conceptual work to guide the design of assessment and learning in an adaptive environment.Although adaptive learning might have been touted as a universal cure for learning problems,many adaptive language learning systems fall short of educators’expectations,partly due to a lack of standards and best practices in this area.To fill this gap,this paper proposes some major considerations in designing a high-quality assessment and learning experience in adaptive learning and ways to evaluate an adaptive learning system.The architecture of adaptive learning is decomposed,with a chain of inferences supporting the overall efficacy of an adaptive learning system presented,including user property representation,user property estimation,content representation,user interaction representation,and user interaction impact.A detailed analysis of key validity issues is provided for each inference,which motivates the major considerations in designing and evaluating assessment and learning.The paper first provides an overview of different types of assessment used in adaptive learning and an analysis of the assessment approach,priorities,and design considerations of each to optimize its use in adaptive learning.Then it proposes a framework for evaluating different aspects of an adaptive learning system.Some special connections are made to models,techniques,designs,and technologies specific to language learning and assessment,bringing more relevance to adaptive language learning solutions.Through establishing some guidelines on key aspects to evaluate and how to evaluate them,the work intends to bring more rigor to the field of adaptive language learning systems.

An efficient cross-layer buffer management optimization scheme for 5G protocol stack

It is extremely challenging for the 5G User Equipment(UE)to meet the requirement of low-latency data transmission with higher achievable data rates.And user plane processing of 5G protocol stack(PS)is one of the dominating components for end-to-end data transmission in the network system.In this paper,a cross-layer buffer management scheme(CLBM)is proposed.CLBM adopts a zero-copy technique for protocol data unit(PDU)processing between protocol layers and allows to improve the memory operation efficiency significantly with reduced processing latency and CPU usage.Moreover,the PS performance profiling(PSperf)tool,a general evaluation framework for the performance measurement and analysis of PS,is implemented based on the OpenAirInterface(OAI)5G platform.The evaluation result shows that compared with the PS of OAI the CLBM strategy reduces the CPU usage of RLC,PDCP,and MAC layer processing significantly up to 20.6%,63.4%,and 38.8%,respectively.In result,the processing delay of the whole user plane of PS also has been reduced distinctly at various offered traffic load.

Mining Metrics for Enhancing E-Commerce Systems User Experience

The diversity of e-commerce Business to Consumer systems and the significant increase in their use during the COVID-19 pandemic as a one of the primary channels of retail commerce, has made all the most important the need to measuring their quality using practical methods. This paper presents a quality evaluation framework for web metrics that are B2C specific. The framework uses three dimensions based on end-user interaction categories, metrics internal specs and quality sub-characteristics as defined by ISO25010. Beginning from the existing large corpus of general-purpose web metrics, e-commerce specific metrics are chosen and categorized. Analysis results are subjected to a data mining analysis to provide association rules between the various dimensions of the framework. Finally, an ontology that corresponds to the framework is developed to answer to complicated questions related to metrics use and to facilitate the production of new, user defined meta-metrics.

Deep-learning architecture for PM_(2.5) concentration prediction: A review

Accurately predicting the concentration of fine particulate matter(PM_(2.5))is crucial for evaluating air pollution levels and public exposure.Recent advancements have seen a significant rise in using deep learning(DL)models for forecasting PM_(2.5) concentrations.Nonetheless,there is a lack of unified and standardized frameworks for assessing the performance of DL-based PM_(2.5) prediction models.Here we extensively reviewed those DL-based hybrid models for forecasting PM_(2.5) levels according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses(PRISMA)guidelines.We examined the similarities and differences among various DL models in predicting PM_(2.5) by comparing their complexity and effectiveness.We categorized PM_(2.5) DL methodologies into seven types based on performance and application conditions,including four types of DL-based models and three types of hybrid learning models.Our research indicates that established deep learning architectures are commonly used and respected for their efficiency.However,many of these models often fall short in terms of innovation and interpretability.Conversely,models hybrid with traditional approaches,like deterministic and statistical models,exhibit high interpretability but compromise on accuracy and speed.Besides,hybrid DL models,representing the pinnacle of innovation among the studied models,encounter issues with interpretability.We introduce a novel three-dimensional evaluation framework,i.e.,Dataset-MethodExperiment Standard(DMES)to unify and standardize the evaluation for PM_(2.5) predictions using DL models.This review provides a framework for future evaluations of DL-based models,which could inspire researchers to standardize DL model usage in PM_(2.5) prediction and improve the quality of related studies.

Quality assessment in competition-based software crowdsourcing

Quality assessment is a critical component incrowdsourcing-based software engineering(CBSE)as soft-ware products arc developed by the crowd with unknownor varied skills and motivations.In this paper.we proposea novel metric called the project score to measure the perfor-mance of projects and the quality of products for compctition-based software crowdsourcing devclopment(CBSCD)activ-ities.To the best of our knowledge,this is the first work to deal with the quality issue of CBSE in the perspective ofprojccts instead of contcsts.In particular,we develop a hi-crarchical quality evaluation framework for CBSCD projects and come up with two metric aggregatibn modcls for projectscores.The first model is a modified squale model that canlocate the sofiware modules of poor quality,and the secondone is a clustering-based aggregation model,which takes dif-ferent impacts of phases into account.To test the effective-ness of the proposed metrics.we conduct an empirical studyon TopCoder,which is a famous CBSCD platform.Resultsshow that the proposed project score is a strong indicator ofthe performance and product quality of CBSCD projects.wealso find that the clustering-based aggregation model outpcr-forms the Squale one by increasing the percentage of the per-formance evaluation criterion of aggregation models by anadditional 29%.Our approach to quality assessment for CB-sCD projects could potentially facilitate software managersto assess the overall quality of a crowdsourced project con-sisting of programming contests.