Rule acquisition of three-way semi-concept lattices in formal decision context

Three-way concept analysis is an important tool for information processing,and rule acquisition is one of the research hotspots of three-way concept analysis.However,compared with three-way concept lattices,three-way semi-concept lattices have three-way operators with weaker constraints,which can generate more concepts.In this article,the problem of rule acquisition for three-way semi-concept lattices is discussed in general.The authors construct the finer relation of three-way semi-concept lattices,and propose a method of rule acquisition for three-way semi-concept lattices.The authors also discuss the set of decision rules and the relationships of decision rules among object-induced three-way semi-concept lattices,object-induced three-way concept lattices,classical concept lattices and semi-concept lattices.Finally,examples are provided to illustrate the validity of our conclusions.

Value and Measures of Integrating Local Red Culture into the Ideological and Political Course of Environmental Disciplines under the OBE Concept

Based on output-oriented education,the OBE(Outcome-Based Education)concept integrates local red culture into the ideological and political course of environmental disciplines,and is an important part of training applied talents of environmental disciplines in the new era.This educational model makes an innovation on the traditional educational and teaching concepts and centers on students.This paper analyzes the value of integrating local red culture into the ideological and political course under the OBE concept,and puts forward an effective implementation path.

Performance Evaluation of Low-Carbon and Clean Transformation of China’s Coal Economy

In China,the oversupply of coal occurred in 2009,and from that year onwards,China’s coal economy began a low-carbon and clean transformation.Evaluating transformation performance is the research goal of this paper.The data collection for this paper includes data on deep processing of Chinese coal products from 2009 to 2020,as well as data on asset structure evolution and financial performance of 34 listed companies in the Chinese coal mining.Entropy value method is used to calculate the entropy value of low-carbon transformation,and the regression analysis is used to study the performance of cleaner transformation,the conclusion is as follows:(1)From 2009 to 2020,in China’s total energy consumption,coal consumption accounted for 71.6%in 2009 and 56.8%in 2020,the goals set by the state have been achieved.(2)The national goal of reducing the proportion of coal consumption and reducing carbon emissions has forced the transformation of deep processing of coal products.The transformation of coal enterprises towards low-carbon and clean production has achieved remarkable results.(3)From 2009 to 2020,the non coal industry income of 34 listed companies in China’s coal mining industry increased by 8.21%annually.At the same time,the asset structure was adjusted,and nearly 80%of the asset structure evolution showed an orderly development trend.(4)The regression analysis results show that the entropy value of coal deep processing products and the entropy value of asset structure adjustment are significantly related to transformation performance.The paper proposes to summarize the successful experience of China’s coal energy economic transformation,lay a foundation for achieving the carbon peak and carbon neutral goals in the future,further increase the intensity of coal deep processing,increase the proportion of clean energy in total energy consumption,and strive to control asset operation towards the goal of increasing the proportion of non coal industry income.

The Sustainable Development Pathway of the Biomedical Industry Based on Environmental,Social,and Governance(ESG)Concepts

There is a growing global awareness of environmental,social,and governance(ESG)concerns.The biopharmaceutical industry is an important field that affects human health and well-being,and its sustainable development is now the industry’s focus.Based on the current state of the green development of China’s biopharmaceutical industry,the article proposes suggestions and paths for promoting the industry to better fulfill its social responsibilities and protect the environment while pursuing economic benefits.By doing so,the industry can make a greater contribution to global public health and become an important factor in promoting human health and social prosperity.

Progress in The Application of Nursing Care Based on ERAS Concept after Thoracolumbar Fracture Surgery

Thoracic spine fracture is a common orthopedic injury that is usually caused by external forces acting directly on or transmitted to the thoracic spine through other parts of the spine.Thoracic spine fractures can be divided into two types:stable and unstable.An unstable fracture means that the relationship between the vertebral bodies is no longer stable,which may cause serious consequences such as spinal compression,nerve root compression,or spinal cord injury.Surgical treatment is often needed for patients with unstable fractures,nerve root compression,or spinal cord injury to restore stability and function to the thoracic spine.The probability of complications after thoracolumbar fracture surgery is high,which affects the outcome of surgical treatment.To improve postoperative rehabilitation outcomes,this article analyzed the value of nursing care based on the enhanced recovery after surgery(ERAS)concept for patients undergoing thoracolumbar fracture surgery.

Mountain Highway Design Based on New Green Design Concepts

This article analyzes the implementation of new environmentally friendly design practices in the construction of mountain highways.It covers topics such as green highway design concepts,alignment principles,and green practices specifically for mountainous highway design.This analysis aims to provide useful insights for creating green mountain highways that meet the demands of modern times.

Reform of Hospitality English Teaching Based on the Educational Concept of Outcome-Based Education(OBE)

The Outcome-Based Education(OBE)educational concept,proposed by renowned American educator Spady,aims to guide students in mastering learning laws and ultimately achieving expected learning outcomes.The application of OBE educational concept in Hospitality English curriculum not only can effectively enhance the learning effect but also promote the reform of the Hospitality English curriculum,thus improving students’learning enthusiasm.Therefore,taking the Hospitality English curriculum as an example,this paper points out the existing problems in the teaching of this course and suggests the reform measures based on the OBE teaching concept,hoping to provide guidelines for related educational work.

Plasma-electrified up-carbonization for low-carbon clean energy

Low-value,renewable,carbon-rich resources,with different biomass feedstocks and their derivatives as typical examples,represent virtually inexhaustive carbon sources and carbon-related energy on Earth.Upon conversion to higher-value forms(referred to as“up-carbonization”here),these abundant feedstocks provide viable opportunities for energy-rich fuels and sustainable platform chemicals production.However,many of the current methods for such up-carbonization still lack sufficient energy,cost,and material efficiency,which affect their economics and carbon-emissions footprint.With external electricity precisely delivered,discharge plasmas enable many stubborn reactions to occur under mild conditions,by creating locally intensified and highly reactive environments.This technology emerges as a novel,versatile technology platform for integrated or stand-alone conversion of carbon-rich resources.The plasma-based processes are compatible for integration with increasingly abundant and cost-effective renewable electricity,making the whole conversion carbon-neutral and further paving the plasma-electrified upcarbonization to be performance-,environment-,and economics-viable.Despite the chief interest in this emerging area,no review article brings together the state-of-the-art results from diverse disciplines and underlies basic mechanisms and chemistry underpinned.As such,this review aims to fill this gap and provide basic guidelines for future research and transformation,by providing an overview of the application of plasma techniques for carbon-rich resource conversion,with particular focus on the perspective of discharge plasmas,the fundamentals of why plasmas are particularly suited for upcarbonization,and featured examples of plasma-enabled resource valorization.With parallels drawn and specificity highlighted,we also discuss the technique shortcomings,current challenges,and research needs for future work.

The Low-Carbon Transition of Energy Systems:A Bibliometric Review from an Engineering Management Perspective

As a major solution to climate change,the low-carbon transition of energy systems has received growing attention in the past decade.This paper presents a bibliometric review of the literature on the low-carbon transition of energy systems from an engineering management perspective.First,the definition and boundaries of the energy system transition are clarified,covering transformation of the energy structure,decarbonization of fossil fuel utilization,and improvement in energy efficiency.Second,a systematic search of the related literature and a bibliometric analysis are conducted to reveal the research trends.It is found that the number of related publications has been growing exponentially during the past decade,with researchers from China,the United Kingdom,the United States,Germany,and the Netherlands comprising the majority of authors.Related studies with interdisciplinary characteristics appear in journals focusing on energy engineering,environmental science,and social science related to energy issues.Four major research themes are identified by clustering the existing literature:(1)low-carbon transition pathways with different spatiotemporal scales and transition constraints;(2)low-carbon technology diffusion with a focus on renewable energy technologies,pollution control technologies,and other technologies facilitating the energy transition;(3)infrastructure network planning for energy systems covering various sectors and regions;and(4)transition-driving mechanisms from the political,economic,social,and natural perspectives.These four topics play distinct but mutually supportive roles in facilitating the low-carbon transition of energy systems,and require more in-depth research on designing resilient low-carbon transition pathways with coordinated goals,promoting low-carbon technologies with cost-effective and reliable infrastructure network deployment,and balancing multi-level risks in various systems.Finally,business models,nongovernment actors,energy justice,deep decarbonization,and zero-energy buildings are recognized as emerging hot topics.

An Intelligent Control Method for the Low-Carbon Operation of Energy-Intensive Equipment

Based on an analysis of the operational control behavior of operation experts on energy-intensive equipment,this paper proposes an intelligent control method for low-carbon operation by combining mechanism analysis with deep learning,linking control and optimization with prediction,and integrating decision-making with control.This method,which consists of setpoint control,self-optimized tuning,and tracking control,ensures that the energy consumption per tonne is as low as possible,while remaining within the target range.An intelligent control system for low-carbon operation is developed by adopting the end-edge-cloud collaboration technology of the Industrial Internet.The system is successfully applied to a fused magnesium furnace and achieves remarkable results in reducing carbon emissions.

Dynamic decision and its complex dynamics analysis of low-carbon supply chain considering risk-aversion under carbon tax policy

This study establishes a low-carbon supply chain game model under the centralized decision situation and the decentralized decision situation considering the manufacturer risk-aversion behavior, and discusses the influence of the manufacturer risk-aversion behavior on the optimal decision, profit, coordination, and complex dynamics of the supply chain. We find that comparing with the risk-neutral decentralized decision, the increase of manufacturer's risk tolerance attitude can narrow the gap between the supply chain profit and the centralized decision, but it will further reduce the carbon emission reduction level. The increase of risk tolerance of the manufacturer and carbon tax will narrow the stable region of the system. Under this situation, the manufacturer should carefully adjust parameters to prevent the system from losing stability,especially the adjustment parameters for carbon emission reduction level. When the system is in a chaotic state, the increase of carbon tax rate makes the system show more complex dynamic characteristics. Under the chaotic state, it is difficult for the manufacturer to make correct price decision and carbon emission reduction strategy for the next period, which damages its profit, but increases the profit of the retailer and the supply chain. Finally, the carbon emission reduction cost-sharing contract is proposed to improve the carbon emission reduction level and the supply chain efficiency, achieving Pareto improvement. The stability region of the system is larger than that in the centralized decision situation, but the increase of the cost sharing coefficient will reduce the stability of the system in the decentralized decision-making situation.

Core Competitiveness Construction of Clothing Brands in Low-Carbon Economy

The climate issue has become an environmental concern for all sectors of the world and the low-carbon economy has thus become a new economic development model to combat climate change.With the development of low-carbon economy era,the textile and clothing industry plays an important role in stabilizing the development of low-carbon economy and society,and China has put forward the development requirements of low-carbon transformation for the textile and clothing industry,and also it has an important strategic value to promote the high-quality development of low-carbon economy and society,and the construction of brands’ core competitiveness is an inevitable choice for clothing brands in the face of the new form of international competition.As a result,the evaluation indicator of clothing brands’ core competitiveness in the low-carbon economy is used to measure the core competitiveness of clothing brands.Based on the corresponding verification results obtained by analytic hierarchy process(AHP) analysis,it can guide the low-carbon development of the clothing industry,thus proposing a more reasonable way to build the core competitiveness of clothing brands.It can promote the low-carbon transformation and upgrading of the clothing industry,effectively increase the market share of clothing brands,and promote the high-quality development of clothing brands.

Cold plasma-activated Cu-Co catalysts with CN vacancies for enhancing CO_(2)electroreduction to low-carbon alcohol

Electrocatalytic CO_(2)reduction reaction to low-carbon alcohol is a challenging task,especially high selectivity for ethanol,which is mainly limited by the regulation of reaction intermediates and subsequent C–C coupling.A Cu-Co bimetallic catalyst with CN vacancies is successfully developed by H_(2)cold plasma toward a high-efficiency CO_(2)RR into low-carbon alcohol.The Cu-Co PBA-V_(CN)(Prussian blue analogues with CN vacancies)electrocatalyst yields methanol and ethanol as major products with a total low-carbon alcohol FE of 83.8%(methanol:39.2%,ethanol:44.6%)at-0.9 V vs.RHE,excellent durability(100 h)and a small onset potential of-0.21 V.ATR-SEIRAS(attenuated total internal reflection surface enhanced infrared absorption spectroscopy)and DFT(density functional theory)reveal that the steric hindrance of V_(CN)can enhance the CO generation from*COOH,and the C–C coupling can also be increased by CO spillover on uniformly dispersed Cu atoms.This work provides a strategy for the design and preparation of electrocatalysts for CO_(2)RR into low-carbon alcohol products and highlights the impact of catalyst steric hindrance to catalytic performance.

Risk preferences and the low-carbon agricultural technology adoption:Evidence from rice production in China

Climate change which is mainly caused by carbon emissions is a global problem affecting the economic development and well-being of human society.Low-carbon agriculture is of particular significance in slowing down global warming and reaching the goal of“carbon peak and carbon neutrality”.Therefore,taking straw incorporation as an example,this paper aims to investigate the impact of risk preferences on farmers’low-carbon agricultural technology(LCAT)adoption.Based on a two-phase micro-survey data of 1038 rice farmers in Jiangsu,Jiangxi,and Hunan provinces,this paper uses experimental economics methods to measure farmers’risk aversion and loss aversion to obtain the real risk preferences information of the farmers.We also explore the data to examine the actual LCAT adoption behavior of farmers.The results revealed that both risk aversion and loss aversion significantly inhibit farmers’LCAT adoption:more risk-averse or more loss-averse farmers are less likely to adopt LCAT.It is further found that crop insurance,farm scale and governmental regulations can alleviate the negative impact of risk aversion and loss aversion on farmers’LCAT adoption.Therefore,we propose that local governments need to promote low-carbon agricultural development by propagating the benefits of LCAT,extending crop insurance,promoting appropriate scale operations,and strengthening governmental regulations to promote farmers’LCAT adoption.

Impact of minimalism on consumers’ low-carbon innovation behavior: Interactive role of quantitative behavior

Minimalism has become a new consumer trend that can guide low-carbon innovation behaviors.This study uses two experiments and one survey to explore the mechanisms underlying the relationships among minimalism,quantitative behavior,and low-carbon innovation behavior.The results show that(1)minimalism can positively influence consumers’low-carbon innovation behavior;(2)the interactive effect of minimalist and quantitative behavior on low-carbon innovation behavior is significant;and(3)meaning in life can play a significant mediating role in the relationship between minimalism and low-carbon innovation behavior.Finally,corresponding strategies for theory and management practices are proposed.

Concept Drift Analysis and Malware Attack Detection System Using Secure Adaptive Windowing

Concept drift is a main security issue that has to be resolved since it presents a significant barrier to the deployment of machine learning(ML)models.Due to attackers’(and/or benign equivalents’)dynamic behavior changes,testing data distribution frequently diverges from original training data over time,resulting in substantial model failures.Due to their dispersed and dynamic nature,distributed denial-of-service attacks pose a danger to cybersecurity,resulting in attacks with serious consequences for users and businesses.This paper proposes a novel design for concept drift analysis and detection of malware attacks like Distributed Denial of Service(DDOS)in the network.The goal of this architecture combination is to accurately represent data and create an effective cyber security prediction agent.The intrusion detection system and concept drift of the network has been analyzed using secure adaptive windowing with website data authentication protocol(SAW_WDA).The network has been analyzed by authentication protocol to avoid malware attacks.The data of network users will be collected and classified using multilayer perceptron gradient decision tree(MLPGDT)classifiers.Based on the classification output,the decision for the detection of attackers and authorized users will be identified.The experimental results show output based on intrusion detection and concept drift analysis systems in terms of throughput,end-end delay,network security,network concept drift,and results based on classification with regard to accuracy,memory,and precision and F-1 score.

Combined Effect of Concept Drift and Class Imbalance on Model Performance During Stream Classification

Every application in a smart city environment like the smart grid,health monitoring, security, and surveillance generates non-stationary datastreams. Due to such nature, the statistical properties of data changes overtime, leading to class imbalance and concept drift issues. Both these issuescause model performance degradation. Most of the current work has beenfocused on developing an ensemble strategy by training a new classifier on thelatest data to resolve the issue. These techniques suffer while training the newclassifier if the data is imbalanced. Also, the class imbalance ratio may changegreatly from one input stream to another, making the problem more complex.The existing solutions proposed for addressing the combined issue of classimbalance and concept drift are lacking in understating of correlation of oneproblem with the other. This work studies the association between conceptdrift and class imbalance ratio and then demonstrates how changes in classimbalance ratio along with concept drift affect the classifier’s performance.We analyzed the effect of both the issues on minority and majority classesindividually. To do this, we conducted experiments on benchmark datasetsusing state-of-the-art classifiers especially designed for data stream classification.Precision, recall, F1 score, and geometric mean were used to measure theperformance. Our findings show that when both class imbalance and conceptdrift problems occur together the performance can decrease up to 15%. Ourresults also show that the increase in the imbalance ratio can cause a 10% to15% decrease in the precision scores of both minority and majority classes.The study findings may help in designing intelligent and adaptive solutionsthat can cope with the challenges of non-stationary data streams like conceptdrift and class imbalance.

A low-carbon economic dispatch model for electricity market with wind power based on improved ant-lion optimisation algorithm

Introducing carbon trading into electricity market can convert carbon dioxide into schedulable resources with economic value.However,the randomness of wind power generation puts forward higher requirements for electricity market transactions.Therefore,the carbon trading market is introduced into the wind power market,and a new form of low-carbon economic dispatch model is developed.First,the economic dispatch goal of wind power is be considered.It is projected to save money and reduce the cost of power generation for the system.The model includes risk operating costs to account for the impact of wind power output variability on the system,as well as wind farm negative efficiency operating costs to account for the loss caused by wind abandonment.The model also employs carbon trading market metrics to achieve the goal of lowering system carbon emissions,and analyze the impact of different carbon trading prices on the system.A low-carbon economic dispatch model for the wind power market is implemented based on the following two goals.Finally,the solution is optimised using the Ant-lion optimisation method,which combines Levi's flight mechanism and golden sine.The proposed model and algorithm's rationality is proven through the use of cases.

DEBRA: On the Unsupervised Learning of Concept Hierarchies from (Literary) Text

With this work, we introduce a novel method for the unsupervised learning of conceptual hierarchies, or concept maps as they are sometimes called, which is aimed specifically for use with literary texts, as such distinguishing itself from the majority of research literature on the topic which is primarily focused on building ontologies from a vast array of different types of data sources, both structured and unstructured, to support various forms of AI, in particular, the Semantic Web as envisioned by Tim Berners-Lee. We first elaborate on mutually informing disciplines of philosophy and computer science, or more specifically the relationship between metaphysics, epistemology, ontology, computing and AI, followed by a technically in-depth discussion of DEBRA, our dependency tree based concept hierarchy constructor, which as its name alludes to, constructs a conceptual map in the form of a directed graph which illustrates the concepts, their respective relations, and the implied ontological structure of the concepts as encoded in the text, decoded with standard Python NLP libraries such as spaCy and NLTK. With this work we hope to both augment the Knowledge Representation literature with opportunities for intellectual advancement in AI with more intuitive, less analytical, and well-known forms of knowledge representation from the cognitive science community, as well as open up new areas of research between Computer Science and the Humanities with respect to the application of the latest in NLP tools and techniques upon literature of cultural significance, shedding light on existing methods of computation with respect to documents in semantic space that effectively allows for, at the very least, the comparison and evolution of texts through time, using vector space math.

Two-Stage Low-Carbon Economic Dispatch of Integrated Demand Response-Enabled Integrated Energy System with Ladder-Type Carbon Trading

Driven by the goal of“carbon neutrality”and“emission peak”,effectively controlling system carbon emissions has become significantly important to governments around the world.To this end,a novel two-stage low-carbon economic scheduling framework that considers the coordinated optimization of ladder-type carbon trading and integrated demand response(IDR)is proposed in this paper for the integrated energy system(IES),where the first stage determines the energy consumption plan of users by leveraging the price-based electrical-heat IDR.In contrast,the second stage minimizes the system total cost to optimize the outputs of generations with consideration of the uncertainty of renewables.In addition,to fully exploit the system’s emission reduction potential,a carbon trading cost model with segmented CO_(2) emission intervals is built by introducing a reward-penalty ladder-type carbon trading mechanism,and the flexible thermal comfort elasticity of customers is taken into account by putting forward a predicted mean vote index on the load side.The CPLEX optimizer resolves the two-stage model,and the study results on a modified IES situated in North China show the proposed model can effectively reduce carbon emissions and guarantee economical efficiency operation of the system.