The aim of this paper is to present and analyze the factors, motivations and criteria considered in the decision-making processes of the actors belonging to the biodiesel production chain in Brazil. The biodiesel prod...The aim of this paper is to present and analyze the factors, motivations and criteria considered in the decision-making processes of the actors belonging to the biodiesel production chain in Brazil. The biodiesel production chain consists of three main agents： the farmers, the soybean processing plants and the oil refinery/distributor. For the farmers organized in cooperatives the central decision is whether to sell oil-bearing crops for the production of biodiesel. In contrast, for the soybean processing plants that convert the crops into vegetable and/or biodiesel, the decision to produce this fuel is based on the wish to expand their market portfolio. Government tax incentives strongly influence both decisions regarding which oil-bearing crop to use and the amount of vegetable oil to be transformed into biodiesel. Finally, the oil refinery/distributor is obliged by law to mix the biodiesel with the mineral diesel and perceives this as a liability. The results show the existence of different characteristics linked to the decision-making process and a significant lack of synchronicity in the aims and motivations behind the agents＇ decisions. This state of decisional misalignment leads to heightened uncertainty regarding the sustainability of the Brazilian biodiesel production program.展开更多
Community participation and community based management are topical themes in current policy and discussion revolving around decision-making processes especially those dealing with natural resources management.This rev...Community participation and community based management are topical themes in current policy and discussion revolving around decision-making processes especially those dealing with natural resources management.This review shows that while governments have accepted the need to either cede or devolve control and management of natural resources to the local communities,the communities are not part and parcel of the planning and budgeting which are crucial in decisionmaking.Communities were seen to be more involved in the implementation of natural resource management programs but lacked ownership of the projects.This causes lack of commitment to the programs and at times hostile reaction from the communities.The communities are always at the receiving end when it pertains to losses in the exchange.Community participation was shown to be effective when the local population is involved not as co-operating users but as natural resource managers or owner managers.展开更多
Decision-making is the process of deciding between two or more options in order to take the most appropriate and successful course of action in order to achieve sustainable mangrove management. However, the distinctiv...Decision-making is the process of deciding between two or more options in order to take the most appropriate and successful course of action in order to achieve sustainable mangrove management. However, the distinctiveness of mangrove as an ecosystem, and thus the attendant socio-economic and governance ramifications, causes the idea of decision making to become relatively distinct from other decision making process As a result, the purpose of this research was to evaluate the impact that community engagement plays in the decision-making process as it relates to the establishment of governance norms for sustainable mangrove management in Lamu County. In this study, a correlational research design was applied, and the researchers employed a mixed techniques approach. The target population was 296 respondents. The research used questionnaires and interviews to collect data. A descriptive statistical technique was utilized to perform an inspection and analysis on the data that was gathered. The findings indicated that having awareness about governance standards is beneficial during the process of making decisions. In addition, the findings demonstrated that respondents had the impression that the decision-making process was not done properly. On the other hand, the participants pointed out the positive aspects of the decision-making process and agreed that the participation of both gender was essential for the sustainable management of mangroves. Based on these data, it appeared that full community engagement in decision-making is necessary for sustainable management of mangrove forests.展开更多
With the increasing complexity of industrial automation,planetary gearboxes play a vital role in largescale equipment transmission systems,directly impacting operational efficiency and safety.Traditional maintenance s...With the increasing complexity of industrial automation,planetary gearboxes play a vital role in largescale equipment transmission systems,directly impacting operational efficiency and safety.Traditional maintenance strategies often struggle to accurately predict the degradation process of equipment,leading to excessive maintenance costs or potential failure risks.However,existing prediction methods based on statistical models are difficult to adapt to nonlinear degradation processes.To address these challenges,this study proposes a novel condition-based maintenance framework for planetary gearboxes.A comprehensive full-lifecycle degradation experiment was conducted to collect raw vibration signals,which were then processed using a temporal convolutional network autoencoder with multi-scale perception capability to extract deep temporal degradation features,enabling the collaborative extraction of longperiod meshing frequencies and short-term impact features from the vibration signals.Kernel principal component analysis was employed to fuse and normalize these features,enhancing the characterization of degradation progression.A nonlinear Wiener process was used to model the degradation trajectory,with a threshold decay function introduced to dynamically adjust maintenance strategies,and model parameters optimized through maximum likelihood estimation.Meanwhile,the maintenance strategy was optimized to minimize costs per unit time,determining the optimal maintenance timing and preventive maintenance threshold.The comprehensive indicator of degradation trends extracted by this method reaches 0.756,which is 41.2%higher than that of traditional time-domain features;the dynamic threshold strategy reduces the maintenance cost per unit time to 55.56,which is 8.9%better than that of the static threshold optimization.Experimental results demonstrate significant reductions in maintenance costs while enhancing system reliability and safety.This study realizes the organic integration of deep learning and reliability theory in the maintenance of planetary gearboxes,provides an interpretable solution for the predictive maintenance of complex mechanical systems,and promotes the development of condition-based maintenance strategies for planetary gearboxes.展开更多
The aging process is an inexorable fact throughout our lives and is considered a major factor in develo ping neurological dysfunctions associated with cognitive,emotional,and motor impairments.Aging-associated neurode...The aging process is an inexorable fact throughout our lives and is considered a major factor in develo ping neurological dysfunctions associated with cognitive,emotional,and motor impairments.Aging-associated neurodegenerative diseases are characterized by the progressive loss of neuronal structure and function.展开更多
Based on an analysis of the role of industrial control and optimization technologies in the Industrial Revolution,as well as the current situation and existing problems of operational decision-making(ODM)for industria...Based on an analysis of the role of industrial control and optimization technologies in the Industrial Revolution,as well as the current situation and existing problems of operational decision-making(ODM)for industrial process,this paper introduces the concept of intelligent ODM in industrial process,shapes its future directions,and highlights key technical challenges.By the tight conjoining of and coordination between industrial artificial intelligence(AI)with industrial control and optimization technologies,as well as the Industrial Internet with industrial computer management and control systems,an intelligent operational optimization decision-making methodology is proposed for complex industrial process.The intelligent ODM methodology and its successful application demonstrate that the tight conjoining of and coordination between next-generation information technologies with industrial control and optimization technologies will promote the development of industrial intelligent ODM.Finally,main research directions and ideas are outlined for realizing intelligent ODM in industrial process.展开更多
Selecting fires safety measures for road tunnels relies mainly on strict regulatory requirements. However, the choice should also be based on many different criteria and ranking of alternatives should take place. Exis...Selecting fires safety measures for road tunnels relies mainly on strict regulatory requirements. However, the choice should also be based on many different criteria and ranking of alternatives should take place. Existing methods exhibit lack in dealing rigorously with measures’ selection amongst different alternatives. This paper contributes to the body of knowledge by proposing a novel method, named EVADE, which aims to incorporate diverse stakeholders’ views and provide a meaningful ranking of alternatives.To do so, it estimates the tunnel level of safety taking into account only any standard measures existing. Subsequently, the performance of additional measures is examined.Then, a list of the most significant criteria that are valuable to judge the appropriateness of selected measures is introduced. The relative importance amongst the decision criteria is calculated through the Analytic Hierarchy Process, based on the expert opinion. Sensitivity analysis through Monte Carlo simulation is embedded to allow for a meaningful prioritization of the decision criteria. Thus, the alternatives’ ranking comes as a distribution instead of a single number, providing the decision-maker richer information for selecting the most suitable measure(s) according to the specific tunnel situation. At last, a typical tunnel is examined to showcase the utilization of the method.展开更多
Dear Editor, This letter proposes a multimodal data-driven reinforcement learning-based method for operational decision-making in industrial processes. Due to the frequent fluctuations of feedstock properties and oper...Dear Editor, This letter proposes a multimodal data-driven reinforcement learning-based method for operational decision-making in industrial processes. Due to the frequent fluctuations of feedstock properties and operating conditions in the industrial processes, existing data-driven methods cannot effectively adjust the operational variables. In addition, multimodal data such as images, audio.展开更多
In the coming decades, agricultural systems will have to adapt to tremendous challenges. Behavioral models have important potential to better understand and steer changes toward sustainability brought about by this co...In the coming decades, agricultural systems will have to adapt to tremendous challenges. Behavioral models have important potential to better understand and steer changes toward sustainability brought about by this context. Relying on a literature review, we distinguish incremental changes (extensions of what is already done) and transformational changes, which involve the reorientation of a considerable amount of farming activities. Transformational changes are particularly important in the context of global change. Existing integrated modelling frameworks based on behavioral theories are suited for incremental changes, but remain limited for transformational changes. Qualitative studies provide important insights on two key aspects of transformational changes, learning and social relations, but they have not been explicitly oriented toward computer modelling yet. Based on this literature and three seminal decision-making approaches, we propose a description of transformational change processes in farm decision-making, as a first step toward an implementation in agent-based models.展开更多
Based on analyzing the influences of a slicing scheme on stair-stepping effect, supporting structure, efficiency and deformation, etc. , analytical hierarchical process （AHP） combining with fuzzy synthetic evaluatio...Based on analyzing the influences of a slicing scheme on stair-stepping effect, supporting structure, efficiency and deformation, etc. , analytical hierarchical process （AHP） combining with fuzzy synthetic evaluation is introduced to make decision in slicing schemes for a processing part. The application in determining the slicing scheme for a computer mouse during prototyping shows that the method increases the rationality during decision- making and improves quality and efficiency for the prototyping part.展开更多
一、作为哲学的AI for Process(一)郭为的哲学思想1.郭为是谁郭为是谁?他是一位哲学家。顺便说,他同时还领导着神州数码。为什么说郭为是哲学家呢?因为他在著作中谈到高深的哲学,如“数据如水,奔流不息,无界融合”。他引述古希腊哲学家...一、作为哲学的AI for Process(一)郭为的哲学思想1.郭为是谁郭为是谁?他是一位哲学家。顺便说,他同时还领导着神州数码。为什么说郭为是哲学家呢?因为他在著作中谈到高深的哲学,如“数据如水,奔流不息,无界融合”。他引述古希腊哲学家赫拉克利特所说的“万物流转”,又说“你不能两次踏进同一条河流,因为新的水不断地流过你的身旁”,他所表达的意思是“世界上唯一不变的就是变化”。展开更多
Collision avoidance decision-making models of multiple agents in virtual driving environment are studied. Based on the behavioral characteristics and hierarchical structure of the collision avoidance decision-making i...Collision avoidance decision-making models of multiple agents in virtual driving environment are studied. Based on the behavioral characteristics and hierarchical structure of the collision avoidance decision-making in real life driving, delphi approach and mathematical statistics method are introduced to construct pair-wise comparison judgment matrix of collision avoidance decision choices to each collision situation. Analytic hierarchy process （AHP） is adopted to establish the agents＇ collision avoidance decision-making model. To simulate drivers＇ characteristics, driver factors are added to categorize driving modes into impatient mode, normal mode, and the cautious mode. The results show that this model can simulate human＇s thinking process, and the agents in the virtual environment can deal with collision situations and make decisions to avoid collisions without intervention. The model can also reflect diversity and uncertainly of real life driving behaviors, and solves the multi-objective, multi-choice ranking priority problem in multi-vehicle collision scenarios. This collision avoidance model of multi-agents model is feasible and effective, and can provide richer and closer-to-life virtual scene for driving simulator, reflecting real-life traffic environment more truly, this model can also promote the practicality of driving simulator.展开更多
The critical role of patient-reported outcome measures(PROMs)in enhancing clinical decision-making and promoting patient-centered care has gained a profound significance in scientific research.PROMs encapsulate a pati...The critical role of patient-reported outcome measures(PROMs)in enhancing clinical decision-making and promoting patient-centered care has gained a profound significance in scientific research.PROMs encapsulate a patient's health status directly from their perspective,encompassing various domains such as symptom severity,functional status,and overall quality of life.By integrating PROMs into routine clinical practice and research,healthcare providers can achieve a more nuanced understanding of patient experiences and tailor treatments accordingly.The deployment of PROMs supports dynamic patient-provider interactions,fostering better patient engagement and adherence to tre-atment plans.Moreover,PROMs are pivotal in clinical settings for monitoring disease progression and treatment efficacy,particularly in chronic and mental health conditions.However,challenges in implementing PROMs include data collection and management,integration into existing health systems,and acceptance by patients and providers.Overcoming these barriers necessitates technological advancements,policy development,and continuous education to enhance the acceptability and effectiveness of PROMs.The paper concludes with recommendations for future research and policy-making aimed at optimizing the use and impact of PROMs across healthcare settings.展开更多
To solve problems of poor security guarantee and insufficient training efficiency in the conventional reinforcement learning methods for decision-making,this study proposes a hybrid framework to combine deep reinforce...To solve problems of poor security guarantee and insufficient training efficiency in the conventional reinforcement learning methods for decision-making,this study proposes a hybrid framework to combine deep reinforcement learning with rule-based decision-making methods.A risk assessment model for lane-change maneuvers considering uncertain predictions of surrounding vehicles is established as a safety filter to improve learning efficiency while correcting dangerous actions for safety enhancement.On this basis,a Risk-fused DDQN is constructed utilizing the model-based risk assessment and supervision mechanism.The proposed reinforcement learning algorithm sets up a separate experience buffer for dangerous trials and punishes such actions,which is shown to improve the sampling efficiency and training outcomes.Compared with conventional DDQN methods,the proposed algorithm improves the convergence value of cumulated reward by 7.6%and 2.2%in the two constructed scenarios in the simulation study and reduces the number of training episodes by 52.2%and 66.8%respectively.The success rate of lane change is improved by 57.3%while the time headway is increased at least by 16.5%in real vehicle tests,which confirms the higher training efficiency,scenario adaptability,and security of the proposed Risk-fused DDQN.展开更多
This paper contains research on strategic decision-making in a local government. In a profit-oriented organization, the option that maximizes profits tends involve reaching an agreement between stakeholders. However, ...This paper contains research on strategic decision-making in a local government. In a profit-oriented organization, the option that maximizes profits tends involve reaching an agreement between stakeholders. However, there is tendency for stakeholders to differ in their beliefs as to what is desirable particularly in a non-profit organization. In a local government, it is especially difficult for the interests of a stakeholder group to be completely in agreement. This research considers the use of the analytical hierarchy process （Saaty, 1971） as a solution for one of the difficulties of decision-making in a local government. This research is a case study to explore the strategy of a local Japanese healthcare management organization. The conclusion was drawn to decide which strategic option should be taken by using the analytical hierarchy process. Also, it was found what to work on a countermeasure that prevents the negative effects that are generated by selecting the strategic option.展开更多
Due to the numerous variables to take into account as well as the inherent ambiguity and uncertainty,evaluating educational institutions can be difficult.The concept of a possibility Pythagorean fuzzy hypersoft set(pP...Due to the numerous variables to take into account as well as the inherent ambiguity and uncertainty,evaluating educational institutions can be difficult.The concept of a possibility Pythagorean fuzzy hypersoft set(pPyFHSS)is more flexible in this regard than other theoretical fuzzy set-like models,even though some attempts have been made in the literature to address such uncertainties.This study investigates the elementary notions of pPyFHSS including its set-theoretic operations union,intersection,complement,OR-and AND-operations.Some results related to these operations are also modified for pPyFHSS.Additionally,the similarity measures between pPyFHSSs are formulated with the assistance of numerical examples and results.Lastly,an intelligent decision-assisted mechanism is developed with the proposal of a robust algorithm based on similarity measures for solving multi-attribute decision-making(MADM)problems.A case study that helps the decision-makers assess the best educational institution is discussed to validate the suggested system.The algorithmic results are compared with the most pertinent model to evaluate the adaptability of pPyFHSS,as it generalizes the classical possibility fuzzy set-like theoretical models.Similarly,while considering significant evaluating factors,the flexibility of pPyFHSS is observed through structural comparison.展开更多
Accurate medical diagnosis,which involves identifying diseases based on patient symptoms,is often hindered by uncertainties in data interpretation and retrieval.Advanced fuzzy set theories have emerged as effective to...Accurate medical diagnosis,which involves identifying diseases based on patient symptoms,is often hindered by uncertainties in data interpretation and retrieval.Advanced fuzzy set theories have emerged as effective tools to address these challenges.In this paper,new mathematical approaches for handling uncertainty in medical diagnosis are introduced using q-rung orthopair fuzzy sets(q-ROFS)and interval-valued q-rung orthopair fuzzy sets(IVq-ROFS).Three aggregation operators are proposed in our methodologies:the q-ROF weighted averaging(q-ROFWA),the q-ROF weighted geometric(q-ROFWG),and the q-ROF weighted neutrality averaging(qROFWNA),which enhance decision-making under uncertainty.These operators are paired with ranking methods such as the similarity measure,score function,and inverse score function to improve the accuracy of disease identification.Additionally,the impact of varying q-rung values is explored through a sensitivity analysis,extending the analysis beyond the typical maximum value of 3.The Basic Uncertain Information(BUI)method is employed to simulate expert opinions,and aggregation operators are used to combine these opinions in a group decisionmaking context.Our results provide a comprehensive comparison of methodologies,highlighting their strengths and limitations in diagnosing diseases based on uncertain patient data.展开更多
Current research on heterogeneous advanced oxidation processes(HAOPs)predominantly emphasizes catalyst iteration and innovation.Significant efforts have been made to regulate the electron structure and optimize the el...Current research on heterogeneous advanced oxidation processes(HAOPs)predominantly emphasizes catalyst iteration and innovation.Significant efforts have been made to regulate the electron structure and optimize the electron distribution,thereby increasing the catalytic activity.However,this focus often overshadows an equally essential aspect of HAOPs:the adsorption effect.Adsorption is a critical initiator for triggering the interaction of oxidants and contaminants with heterogeneous catalysts.The efficacy of these interactions is influenced by a variety of physicochemical properties,including surface chemistry and pore sizes,which determine the affinities between contaminants and material surfaces.This dispar ity in affinity is pivotal because it underpins the selective removal of contaminants,especially in complex waste streams containing diverse contaminants and competing matrices.Consequently,understanding and mastering these interfacial interactions is fundamentally indispensable not only for improving pro cess efficiency but also for enhancing the selectivity of contaminant removal.Herein,we highlight the importance of adsorption-driven interfacial interactions for fundamentally elucidating the catalytic mechanisms of HAOPs.Such interactions dictate the overall performance of the treatment processes by balancing the adsorption,reaction,and desorption rates on the catalyst surfaces.Elucidating the adsorption effect not only shifts the paradigm in understanding HAOPs but also improves their practical ity in water treatment and wastewater decontamination.Overall,we propose that revisiting adsorption driven interfacial interactions holds great promise for optimizing catalytic processes to develop effective HAOP strategies.展开更多
BACKGROUND Understanding a patient's clinical status and setting priorities for their care are two aspects of the constantly changing process of clinical decision-making.One analytical technique that can be helpfu...BACKGROUND Understanding a patient's clinical status and setting priorities for their care are two aspects of the constantly changing process of clinical decision-making.One analytical technique that can be helpful in uncertain situations is clinical judgment.Clinicians must deal with contradictory information,lack of time to make decisions,and long-term factors when emergencies occur.AIM To examine the ethical issues healthcare professionals faced during the coronavirus disease 2019(COVID-19)pandemic and the factors affecting clinical decision-making.METHODS This pilot study,which means it was a preliminary investigation to gather information and test the feasibility of a larger investigation was conducted over 6 months and we invited responses from clinicians worldwide who managed patients with COVID-19.The survey focused on topics related to their professional roles and personal relationships.We examined five core areas influencing critical care decision-making:Patients'personal factors,family-related factors,informed consent,communication and media,and hospital administrative policies on clinical decision-making.The collected data were analyzed using the χ^(2) test for categorical variables.RESULTS A total of 102 clinicians from 23 specialties and 17 countries responded to the survey.Age was a significant factor in treatment planning(n=88)and ventilator access(n=78).Sex had no bearing on how decisions were made.Most doctors reported maintaining patient confidentiality regarding privacy and informed consent.Approximately 50%of clinicians reported a moderate influence of clinical work,with many citing it as one of the most important factors affecting their health and relationships.Clinicians from developing countries had a significantly higher score for considering a patient's financial status when creating a treatment plan than their counterparts from developed countries.Regarding personal experiences,some respondents noted that treatment plans and preferences changed from wave to wave,and that there was a rapid turnover of studies and evidence.Hospital and government policies also played a role in critical decision-making.Rather than assessing the appropriateness of treatment,some doctors observed that hospital policies regarding medications were driven by patient demand.CONCLUSION Factors other than medical considerations frequently affect management choices.The disparity in treatment choices,became more apparent during the pandemic.We highlight the difficulties and contradictions between moral standards and the realities physicians encountered during this medical emergency.False information,large patient populations,and limited resources caused problems for clinicians.These factors impacted decision-making,which,in turn,affected patient care and healthcare staff well-being.展开更多
This paper focuses on the preparation of rare earth oxide products from rare earth chloride solutions during the rare earth extraction and separation processes,as well as the recycling of magnesium chloride solutions....This paper focuses on the preparation of rare earth oxide products from rare earth chloride solutions during the rare earth extraction and separation processes,as well as the recycling of magnesium chloride solutions.It proposes the idea of introducing spray pyrolysis technology into the rare earth extraction and separation processes.This paper briefly describes the development history of chloride spray pyrolysis technology,focusing on the research status and application progress of rare earth chloride solution and magnesium chloride solution spray pyrolysis technology,as well as spray pyrolysis equipment.The paper also analyzes the challenges and technical intricacies associated with applying spray pyrolysis technology to chloride solutions in the rare earth extraction and separation processes.Additionally,it explores future trends and proposes strategies to facilitate the full recycling of acids and bases,streamline the process flow,and enhance the prospects for green and low-carbon rare earth metallurgy.展开更多
文摘The aim of this paper is to present and analyze the factors, motivations and criteria considered in the decision-making processes of the actors belonging to the biodiesel production chain in Brazil. The biodiesel production chain consists of three main agents： the farmers, the soybean processing plants and the oil refinery/distributor. For the farmers organized in cooperatives the central decision is whether to sell oil-bearing crops for the production of biodiesel. In contrast, for the soybean processing plants that convert the crops into vegetable and/or biodiesel, the decision to produce this fuel is based on the wish to expand their market portfolio. Government tax incentives strongly influence both decisions regarding which oil-bearing crop to use and the amount of vegetable oil to be transformed into biodiesel. Finally, the oil refinery/distributor is obliged by law to mix the biodiesel with the mineral diesel and perceives this as a liability. The results show the existence of different characteristics linked to the decision-making process and a significant lack of synchronicity in the aims and motivations behind the agents＇ decisions. This state of decisional misalignment leads to heightened uncertainty regarding the sustainability of the Brazilian biodiesel production program.
文摘Community participation and community based management are topical themes in current policy and discussion revolving around decision-making processes especially those dealing with natural resources management.This review shows that while governments have accepted the need to either cede or devolve control and management of natural resources to the local communities,the communities are not part and parcel of the planning and budgeting which are crucial in decisionmaking.Communities were seen to be more involved in the implementation of natural resource management programs but lacked ownership of the projects.This causes lack of commitment to the programs and at times hostile reaction from the communities.The communities are always at the receiving end when it pertains to losses in the exchange.Community participation was shown to be effective when the local population is involved not as co-operating users but as natural resource managers or owner managers.
文摘Decision-making is the process of deciding between two or more options in order to take the most appropriate and successful course of action in order to achieve sustainable mangrove management. However, the distinctiveness of mangrove as an ecosystem, and thus the attendant socio-economic and governance ramifications, causes the idea of decision making to become relatively distinct from other decision making process As a result, the purpose of this research was to evaluate the impact that community engagement plays in the decision-making process as it relates to the establishment of governance norms for sustainable mangrove management in Lamu County. In this study, a correlational research design was applied, and the researchers employed a mixed techniques approach. The target population was 296 respondents. The research used questionnaires and interviews to collect data. A descriptive statistical technique was utilized to perform an inspection and analysis on the data that was gathered. The findings indicated that having awareness about governance standards is beneficial during the process of making decisions. In addition, the findings demonstrated that respondents had the impression that the decision-making process was not done properly. On the other hand, the participants pointed out the positive aspects of the decision-making process and agreed that the participation of both gender was essential for the sustainable management of mangroves. Based on these data, it appeared that full community engagement in decision-making is necessary for sustainable management of mangrove forests.
基金funded by scientific research projects under Grant JY2024B011.
文摘With the increasing complexity of industrial automation,planetary gearboxes play a vital role in largescale equipment transmission systems,directly impacting operational efficiency and safety.Traditional maintenance strategies often struggle to accurately predict the degradation process of equipment,leading to excessive maintenance costs or potential failure risks.However,existing prediction methods based on statistical models are difficult to adapt to nonlinear degradation processes.To address these challenges,this study proposes a novel condition-based maintenance framework for planetary gearboxes.A comprehensive full-lifecycle degradation experiment was conducted to collect raw vibration signals,which were then processed using a temporal convolutional network autoencoder with multi-scale perception capability to extract deep temporal degradation features,enabling the collaborative extraction of longperiod meshing frequencies and short-term impact features from the vibration signals.Kernel principal component analysis was employed to fuse and normalize these features,enhancing the characterization of degradation progression.A nonlinear Wiener process was used to model the degradation trajectory,with a threshold decay function introduced to dynamically adjust maintenance strategies,and model parameters optimized through maximum likelihood estimation.Meanwhile,the maintenance strategy was optimized to minimize costs per unit time,determining the optimal maintenance timing and preventive maintenance threshold.The comprehensive indicator of degradation trends extracted by this method reaches 0.756,which is 41.2%higher than that of traditional time-domain features;the dynamic threshold strategy reduces the maintenance cost per unit time to 55.56,which is 8.9%better than that of the static threshold optimization.Experimental results demonstrate significant reductions in maintenance costs while enhancing system reliability and safety.This study realizes the organic integration of deep learning and reliability theory in the maintenance of planetary gearboxes,provides an interpretable solution for the predictive maintenance of complex mechanical systems,and promotes the development of condition-based maintenance strategies for planetary gearboxes.
文摘The aging process is an inexorable fact throughout our lives and is considered a major factor in develo ping neurological dysfunctions associated with cognitive,emotional,and motor impairments.Aging-associated neurodegenerative diseases are characterized by the progressive loss of neuronal structure and function.
基金supported by the Research Program of the Liaoning Liaohe Laboratory(LLL23ZZ-05-012)China Academy of Engineering Institute of Land Cooperation Consulting Project(2023-DFZD-60-02)+3 种基金the Key Research and Development Program of Liaoning Province(2023JH26/10200011)the National Natural Science Foundation of China(61991404)the National Key Research and Development Program of China(2024YFB3309700)the Science and Technology Major Project 2024 of Liaoning Province(2024JH1/11700048).
文摘Based on an analysis of the role of industrial control and optimization technologies in the Industrial Revolution,as well as the current situation and existing problems of operational decision-making(ODM)for industrial process,this paper introduces the concept of intelligent ODM in industrial process,shapes its future directions,and highlights key technical challenges.By the tight conjoining of and coordination between industrial artificial intelligence(AI)with industrial control and optimization technologies,as well as the Industrial Internet with industrial computer management and control systems,an intelligent operational optimization decision-making methodology is proposed for complex industrial process.The intelligent ODM methodology and its successful application demonstrate that the tight conjoining of and coordination between next-generation information technologies with industrial control and optimization technologies will promote the development of industrial intelligent ODM.Finally,main research directions and ideas are outlined for realizing intelligent ODM in industrial process.
文摘Selecting fires safety measures for road tunnels relies mainly on strict regulatory requirements. However, the choice should also be based on many different criteria and ranking of alternatives should take place. Existing methods exhibit lack in dealing rigorously with measures’ selection amongst different alternatives. This paper contributes to the body of knowledge by proposing a novel method, named EVADE, which aims to incorporate diverse stakeholders’ views and provide a meaningful ranking of alternatives.To do so, it estimates the tunnel level of safety taking into account only any standard measures existing. Subsequently, the performance of additional measures is examined.Then, a list of the most significant criteria that are valuable to judge the appropriateness of selected measures is introduced. The relative importance amongst the decision criteria is calculated through the Analytic Hierarchy Process, based on the expert opinion. Sensitivity analysis through Monte Carlo simulation is embedded to allow for a meaningful prioritization of the decision criteria. Thus, the alternatives’ ranking comes as a distribution instead of a single number, providing the decision-maker richer information for selecting the most suitable measure(s) according to the specific tunnel situation. At last, a typical tunnel is examined to showcase the utilization of the method.
基金supported by the National Key Research and Development Program of China (2020YFB1713800)the National Natural Science Foundation of China (92267205)+1 种基金the Hunan Provincial Innovation Foundation for Postgraduate (CX2022 0267)the Fundamental Research Funds for the Central Universities of Central South University (2022ZZTS0181)。
文摘Dear Editor, This letter proposes a multimodal data-driven reinforcement learning-based method for operational decision-making in industrial processes. Due to the frequent fluctuations of feedstock properties and operating conditions in the industrial processes, existing data-driven methods cannot effectively adjust the operational variables. In addition, multimodal data such as images, audio.
文摘In the coming decades, agricultural systems will have to adapt to tremendous challenges. Behavioral models have important potential to better understand and steer changes toward sustainability brought about by this context. Relying on a literature review, we distinguish incremental changes (extensions of what is already done) and transformational changes, which involve the reorientation of a considerable amount of farming activities. Transformational changes are particularly important in the context of global change. Existing integrated modelling frameworks based on behavioral theories are suited for incremental changes, but remain limited for transformational changes. Qualitative studies provide important insights on two key aspects of transformational changes, learning and social relations, but they have not been explicitly oriented toward computer modelling yet. Based on this literature and three seminal decision-making approaches, we propose a description of transformational change processes in farm decision-making, as a first step toward an implementation in agent-based models.
基金Supported by the Science and Technology Support Key Project of Jiangsu Province (DE2008365)~~
文摘Based on analyzing the influences of a slicing scheme on stair-stepping effect, supporting structure, efficiency and deformation, etc. , analytical hierarchical process （AHP） combining with fuzzy synthetic evaluation is introduced to make decision in slicing schemes for a processing part. The application in determining the slicing scheme for a computer mouse during prototyping shows that the method increases the rationality during decision- making and improves quality and efficiency for the prototyping part.
文摘一、作为哲学的AI for Process(一)郭为的哲学思想1.郭为是谁郭为是谁?他是一位哲学家。顺便说,他同时还领导着神州数码。为什么说郭为是哲学家呢?因为他在著作中谈到高深的哲学,如“数据如水,奔流不息,无界融合”。他引述古希腊哲学家赫拉克利特所说的“万物流转”,又说“你不能两次踏进同一条河流,因为新的水不断地流过你的身旁”,他所表达的意思是“世界上唯一不变的就是变化”。
基金supported by National Basic Research Program (973 Program,No.2004CB719402)National Natural Science Foundation of China (No.60736019)Natural Science Foundation of Zhejiang Province, China(No.Y105430).
文摘Collision avoidance decision-making models of multiple agents in virtual driving environment are studied. Based on the behavioral characteristics and hierarchical structure of the collision avoidance decision-making in real life driving, delphi approach and mathematical statistics method are introduced to construct pair-wise comparison judgment matrix of collision avoidance decision choices to each collision situation. Analytic hierarchy process （AHP） is adopted to establish the agents＇ collision avoidance decision-making model. To simulate drivers＇ characteristics, driver factors are added to categorize driving modes into impatient mode, normal mode, and the cautious mode. The results show that this model can simulate human＇s thinking process, and the agents in the virtual environment can deal with collision situations and make decisions to avoid collisions without intervention. The model can also reflect diversity and uncertainly of real life driving behaviors, and solves the multi-objective, multi-choice ranking priority problem in multi-vehicle collision scenarios. This collision avoidance model of multi-agents model is feasible and effective, and can provide richer and closer-to-life virtual scene for driving simulator, reflecting real-life traffic environment more truly, this model can also promote the practicality of driving simulator.
文摘The critical role of patient-reported outcome measures(PROMs)in enhancing clinical decision-making and promoting patient-centered care has gained a profound significance in scientific research.PROMs encapsulate a patient's health status directly from their perspective,encompassing various domains such as symptom severity,functional status,and overall quality of life.By integrating PROMs into routine clinical practice and research,healthcare providers can achieve a more nuanced understanding of patient experiences and tailor treatments accordingly.The deployment of PROMs supports dynamic patient-provider interactions,fostering better patient engagement and adherence to tre-atment plans.Moreover,PROMs are pivotal in clinical settings for monitoring disease progression and treatment efficacy,particularly in chronic and mental health conditions.However,challenges in implementing PROMs include data collection and management,integration into existing health systems,and acceptance by patients and providers.Overcoming these barriers necessitates technological advancements,policy development,and continuous education to enhance the acceptability and effectiveness of PROMs.The paper concludes with recommendations for future research and policy-making aimed at optimizing the use and impact of PROMs across healthcare settings.
基金Supported by National Key Research and Development Program of China(Grant No.2022YFE0117100)National Science Foundation of China(Grant No.52102468,52325212)Fundamental Research Funds for the Central Universities。
文摘To solve problems of poor security guarantee and insufficient training efficiency in the conventional reinforcement learning methods for decision-making,this study proposes a hybrid framework to combine deep reinforcement learning with rule-based decision-making methods.A risk assessment model for lane-change maneuvers considering uncertain predictions of surrounding vehicles is established as a safety filter to improve learning efficiency while correcting dangerous actions for safety enhancement.On this basis,a Risk-fused DDQN is constructed utilizing the model-based risk assessment and supervision mechanism.The proposed reinforcement learning algorithm sets up a separate experience buffer for dangerous trials and punishes such actions,which is shown to improve the sampling efficiency and training outcomes.Compared with conventional DDQN methods,the proposed algorithm improves the convergence value of cumulated reward by 7.6%and 2.2%in the two constructed scenarios in the simulation study and reduces the number of training episodes by 52.2%and 66.8%respectively.The success rate of lane change is improved by 57.3%while the time headway is increased at least by 16.5%in real vehicle tests,which confirms the higher training efficiency,scenario adaptability,and security of the proposed Risk-fused DDQN.
文摘This paper contains research on strategic decision-making in a local government. In a profit-oriented organization, the option that maximizes profits tends involve reaching an agreement between stakeholders. However, there is tendency for stakeholders to differ in their beliefs as to what is desirable particularly in a non-profit organization. In a local government, it is especially difficult for the interests of a stakeholder group to be completely in agreement. This research considers the use of the analytical hierarchy process （Saaty, 1971） as a solution for one of the difficulties of decision-making in a local government. This research is a case study to explore the strategy of a local Japanese healthcare management organization. The conclusion was drawn to decide which strategic option should be taken by using the analytical hierarchy process. Also, it was found what to work on a countermeasure that prevents the negative effects that are generated by selecting the strategic option.
基金supported by the Deanship of Graduate Studies and Scientific Research at Qassim University(QU-APC-2024-9/1).
文摘Due to the numerous variables to take into account as well as the inherent ambiguity and uncertainty,evaluating educational institutions can be difficult.The concept of a possibility Pythagorean fuzzy hypersoft set(pPyFHSS)is more flexible in this regard than other theoretical fuzzy set-like models,even though some attempts have been made in the literature to address such uncertainties.This study investigates the elementary notions of pPyFHSS including its set-theoretic operations union,intersection,complement,OR-and AND-operations.Some results related to these operations are also modified for pPyFHSS.Additionally,the similarity measures between pPyFHSSs are formulated with the assistance of numerical examples and results.Lastly,an intelligent decision-assisted mechanism is developed with the proposal of a robust algorithm based on similarity measures for solving multi-attribute decision-making(MADM)problems.A case study that helps the decision-makers assess the best educational institution is discussed to validate the suggested system.The algorithmic results are compared with the most pertinent model to evaluate the adaptability of pPyFHSS,as it generalizes the classical possibility fuzzy set-like theoretical models.Similarly,while considering significant evaluating factors,the flexibility of pPyFHSS is observed through structural comparison.
文摘Accurate medical diagnosis,which involves identifying diseases based on patient symptoms,is often hindered by uncertainties in data interpretation and retrieval.Advanced fuzzy set theories have emerged as effective tools to address these challenges.In this paper,new mathematical approaches for handling uncertainty in medical diagnosis are introduced using q-rung orthopair fuzzy sets(q-ROFS)and interval-valued q-rung orthopair fuzzy sets(IVq-ROFS).Three aggregation operators are proposed in our methodologies:the q-ROF weighted averaging(q-ROFWA),the q-ROF weighted geometric(q-ROFWG),and the q-ROF weighted neutrality averaging(qROFWNA),which enhance decision-making under uncertainty.These operators are paired with ranking methods such as the similarity measure,score function,and inverse score function to improve the accuracy of disease identification.Additionally,the impact of varying q-rung values is explored through a sensitivity analysis,extending the analysis beyond the typical maximum value of 3.The Basic Uncertain Information(BUI)method is employed to simulate expert opinions,and aggregation operators are used to combine these opinions in a group decisionmaking context.Our results provide a comprehensive comparison of methodologies,highlighting their strengths and limitations in diagnosing diseases based on uncertain patient data.
基金supported by the National Key Research and Development Program of China(2022YFC3205300)the National Natural Science Foundation of China(22176124).
文摘Current research on heterogeneous advanced oxidation processes(HAOPs)predominantly emphasizes catalyst iteration and innovation.Significant efforts have been made to regulate the electron structure and optimize the electron distribution,thereby increasing the catalytic activity.However,this focus often overshadows an equally essential aspect of HAOPs:the adsorption effect.Adsorption is a critical initiator for triggering the interaction of oxidants and contaminants with heterogeneous catalysts.The efficacy of these interactions is influenced by a variety of physicochemical properties,including surface chemistry and pore sizes,which determine the affinities between contaminants and material surfaces.This dispar ity in affinity is pivotal because it underpins the selective removal of contaminants,especially in complex waste streams containing diverse contaminants and competing matrices.Consequently,understanding and mastering these interfacial interactions is fundamentally indispensable not only for improving pro cess efficiency but also for enhancing the selectivity of contaminant removal.Herein,we highlight the importance of adsorption-driven interfacial interactions for fundamentally elucidating the catalytic mechanisms of HAOPs.Such interactions dictate the overall performance of the treatment processes by balancing the adsorption,reaction,and desorption rates on the catalyst surfaces.Elucidating the adsorption effect not only shifts the paradigm in understanding HAOPs but also improves their practical ity in water treatment and wastewater decontamination.Overall,we propose that revisiting adsorption driven interfacial interactions holds great promise for optimizing catalytic processes to develop effective HAOP strategies.
文摘BACKGROUND Understanding a patient's clinical status and setting priorities for their care are two aspects of the constantly changing process of clinical decision-making.One analytical technique that can be helpful in uncertain situations is clinical judgment.Clinicians must deal with contradictory information,lack of time to make decisions,and long-term factors when emergencies occur.AIM To examine the ethical issues healthcare professionals faced during the coronavirus disease 2019(COVID-19)pandemic and the factors affecting clinical decision-making.METHODS This pilot study,which means it was a preliminary investigation to gather information and test the feasibility of a larger investigation was conducted over 6 months and we invited responses from clinicians worldwide who managed patients with COVID-19.The survey focused on topics related to their professional roles and personal relationships.We examined five core areas influencing critical care decision-making:Patients'personal factors,family-related factors,informed consent,communication and media,and hospital administrative policies on clinical decision-making.The collected data were analyzed using the χ^(2) test for categorical variables.RESULTS A total of 102 clinicians from 23 specialties and 17 countries responded to the survey.Age was a significant factor in treatment planning(n=88)and ventilator access(n=78).Sex had no bearing on how decisions were made.Most doctors reported maintaining patient confidentiality regarding privacy and informed consent.Approximately 50%of clinicians reported a moderate influence of clinical work,with many citing it as one of the most important factors affecting their health and relationships.Clinicians from developing countries had a significantly higher score for considering a patient's financial status when creating a treatment plan than their counterparts from developed countries.Regarding personal experiences,some respondents noted that treatment plans and preferences changed from wave to wave,and that there was a rapid turnover of studies and evidence.Hospital and government policies also played a role in critical decision-making.Rather than assessing the appropriateness of treatment,some doctors observed that hospital policies regarding medications were driven by patient demand.CONCLUSION Factors other than medical considerations frequently affect management choices.The disparity in treatment choices,became more apparent during the pandemic.We highlight the difficulties and contradictions between moral standards and the realities physicians encountered during this medical emergency.False information,large patient populations,and limited resources caused problems for clinicians.These factors impacted decision-making,which,in turn,affected patient care and healthcare staff well-being.
基金supported by the National Key Research and Development Program of China(2022YFB3504501)the National Natural Science Foundation of China(52274355)。
文摘This paper focuses on the preparation of rare earth oxide products from rare earth chloride solutions during the rare earth extraction and separation processes,as well as the recycling of magnesium chloride solutions.It proposes the idea of introducing spray pyrolysis technology into the rare earth extraction and separation processes.This paper briefly describes the development history of chloride spray pyrolysis technology,focusing on the research status and application progress of rare earth chloride solution and magnesium chloride solution spray pyrolysis technology,as well as spray pyrolysis equipment.The paper also analyzes the challenges and technical intricacies associated with applying spray pyrolysis technology to chloride solutions in the rare earth extraction and separation processes.Additionally,it explores future trends and proposes strategies to facilitate the full recycling of acids and bases,streamline the process flow,and enhance the prospects for green and low-carbon rare earth metallurgy.
