Multi-criteria decision-making(MCDM)is essential for handling complex decision problems under uncertainty,especially in fields such as criminal justice,healthcare,and environmental management.Traditional fuzzy MCDM te...Multi-criteria decision-making(MCDM)is essential for handling complex decision problems under uncertainty,especially in fields such as criminal justice,healthcare,and environmental management.Traditional fuzzy MCDM techniques have failed to deal with problems where uncertainty or vagueness is involved.To address this issue,we propose a novel framework that integrates group and overlap functions with Aczel-Alsina(AA)operational laws in the intuitionistic fuzzy set(IFS)environment.Overlap functions capture the degree to which two inputs share common features and are used to find how closely two values or criteria match in uncertain environments,while the Group functions are used to combine different expert opinions into a single collective result.This study introduces four new aggregation operators:Group Overlap function-based intuitionistic fuzzy Aczel-Alsina(GOF-IFAA)Weighted Averaging(GOF-IFAAWA)operator,intuitionistic fuzzy Aczel-Alsina(GOF-IFAA)Weighted Geometric(GOF-IFAAWG),intuitionistic fuzzy Aczel-Alsina(GOF-IFAA)OrderedWeighted Averaging(GOF-IFAAOWA),and intuitionistic fuzzy Aczel-Alsina(GOF-IFAA)Ordered Weighted Geometric(GOF-IFAAOWG),which are rigorously defined and mathematically analyzed and offer improved flexibility in managing overlapping,uncertain,and hesitant information.The properties of these operators are discussed in detail.Further,the effectiveness,validity,activeness,and ability to capture the uncertain information,the developed operators are applied to the AI-based Criminal Justice Policy Selection problem.At last,the comparison analysis between prior and proposed studies has been displayed,and then followed by the conclusion of the result.展开更多
In this paper,the transferable belief model established on power sets is extended to the permutation event space(PES)and is referred to as the layer-2 transferable belief model.Our goal is to provide a comprehensive a...In this paper,the transferable belief model established on power sets is extended to the permutation event space(PES)and is referred to as the layer-2 transferable belief model.Our goal is to provide a comprehensive approach for handling and modeling uncertainty,capable of representing both quantitative and qualitative information.First,the motivation for proposing the layer-2 transferable belief model and its information processing principles are explored from the perspective of weak propensity.Then,based on these principles,the corresponding information processing methods for the credal and pignistic levels are developed.Finally,the advantages of this model are validated through a classifier that leverages attribute fusion to enhance performance and decision-making accuracy.展开更多
Radio frequency capacitively coupled plasmas(RF CCPs)operated in Ar/O_(2)gas mixtures which are widely adopted in microelectronics,display,and photovoltaic industry,are investigated based on an equivalent circuit mode...Radio frequency capacitively coupled plasmas(RF CCPs)operated in Ar/O_(2)gas mixtures which are widely adopted in microelectronics,display,and photovoltaic industry,are investigated based on an equivalent circuit model coupled with a global model.This study focuses on the effects of singlet metastable molecule O_(2)(b^(1)∑_(8)^(+)),highly excited Herzberg states O_(2)(A^(3)∑_(u)^(+),A^(3)△_(u),c^(1)∑_(u)^(-)),and the negative ion O_(2)^(-),which are usually neglected in simulation studies.Specifically,their impact on particle densities,electronegativity,electron temperature,voltage drop across the sheath,and absorbed power in the discharge is analyzed.The results indicate that O_(2)(b^(1)∑_(8)^(+))and O_(2)^(-)exhibit relatively high densities in argon-oxygen discharges.While O_(2)(A^(3)∑_(u)^(+),A^(3)△_(u),c^(1)∑_(u)^(-))play a critical role in O_(2)b1S+g production,especially at higher pressure.The inclusion of these particles reduces the electronegativity,electron temperature,and key species densities,especially the O^(-)and O^(*)densities.Moreover,the sheath voltage drop,as well as the inductance and resistance of the plasma bulk are enhanced,while the sheath dissipation power and total absorbed power decrease slightly.With the increasing pressure,the influence of these particles on the discharge properties becomes more significant.The study also explores the generation and loss of main neutral species and charged particles within the pressure range of 20 mTorr-100 mTorr(1 Torr=1.33322×10^(2)Pa),offering insights into essential and non-essential reactions for future low-pressure O_(2)and Ar/O_(2)CCP discharge modeling.展开更多
This paper uses Gaussian interval type-2 fuzzy se theory on historical traffic volume data processing to obtain a 24-hour prediction of traffic volume with high precision. A K-means clustering method is used in this p...This paper uses Gaussian interval type-2 fuzzy se theory on historical traffic volume data processing to obtain a 24-hour prediction of traffic volume with high precision. A K-means clustering method is used in this paper to get 5 minutes traffic volume variation as input data for the Gaussian interval type-2 fuzzy sets which can reflect the distribution of historical traffic volume in one statistical period. Moreover, the cluster with the largest collection of data obtained by K-means clustering method is calculated to get the key parameters of type-2 fuzzy sets, mean and standard deviation of the Gaussian membership function.Using the range of data as the input of Gaussian interval type-2 fuzzy sets leads to the range of traffic volume forecasting output with the ability of describing the possible range of the traffic volume as well as the traffic volume prediction data with high accuracy. The simulation results show that the average relative error is reduced to 8% based on the combined K-means Gaussian interval type-2 fuzzy sets forecasting method. The fluctuation range in terms of an upper and a lower forecasting traffic volume completely envelopes the actual traffic volume and reproduces the fluctuation range of traffic flow.展开更多
Objective:To identify alpha-glucosidase inhibitors from Ficus benghalensis and analyze gene set enrichment of regulated protein molecules.Methods:The phytoconstituents of Ficu.s benghalen.sis were queried for inhibito...Objective:To identify alpha-glucosidase inhibitors from Ficus benghalensis and analyze gene set enrichment of regulated protein molecules.Methods:The phytoconstituents of Ficu.s benghalen.sis were queried for inhibitors of alphaglucosidase,also identified as aldose reductase inhibitors.Druglikeness score,absorption,distribution,metabolism,excretion and toxicity profile,biological spectrum,and gene expression were predicated for each compound.Docking study was performed to predict the binding affinity with alpha-glucosidase and aldose reductase and compared with clinically proven molecules.Kyoto Encyclopedia of Genes and Genomes pathway analysis was performed for the regulated genes to identify the modulated pathways.Results:Apigenin,3,4’,5,7-tetrahydroxy-3’-methoxyflavone,and kaempferol were identified as inhibitors of alpha-glucosidase and aldose reductase.Kaempferol was predicted to possess the highest binding affinity with both targets.The p53 signaling pathway was predicted to modulate the majority of protein molecules in diabetes mellitus.All the alpha-glucosidase inhibitors were also predicted as membrane integrity agonist and anti-mutagenic compounds.Conclusions:The current study indicates alpha-glucosidase inhibitors from Ficus benghale,nsis can act as aldose reductase inhibitors after absorption from the intestinal tract.Furthermore,these phytoconstituents are involved in the regulation of numerous protein molecules and pathways.Hence,the anti-diabetic efficacies of these compounds are due to their action on multiple protein molecules and synergistic effects which should be confirmed by future investigations.展开更多
基金supported by“1 Decembrie 1918”University of Alba Iulia,510009 Alba Iuliasupported in part by the HEC-NRPU project,under the grant No.14566.
文摘Multi-criteria decision-making(MCDM)is essential for handling complex decision problems under uncertainty,especially in fields such as criminal justice,healthcare,and environmental management.Traditional fuzzy MCDM techniques have failed to deal with problems where uncertainty or vagueness is involved.To address this issue,we propose a novel framework that integrates group and overlap functions with Aczel-Alsina(AA)operational laws in the intuitionistic fuzzy set(IFS)environment.Overlap functions capture the degree to which two inputs share common features and are used to find how closely two values or criteria match in uncertain environments,while the Group functions are used to combine different expert opinions into a single collective result.This study introduces four new aggregation operators:Group Overlap function-based intuitionistic fuzzy Aczel-Alsina(GOF-IFAA)Weighted Averaging(GOF-IFAAWA)operator,intuitionistic fuzzy Aczel-Alsina(GOF-IFAA)Weighted Geometric(GOF-IFAAWG),intuitionistic fuzzy Aczel-Alsina(GOF-IFAA)OrderedWeighted Averaging(GOF-IFAAOWA),and intuitionistic fuzzy Aczel-Alsina(GOF-IFAA)Ordered Weighted Geometric(GOF-IFAAOWG),which are rigorously defined and mathematically analyzed and offer improved flexibility in managing overlapping,uncertain,and hesitant information.The properties of these operators are discussed in detail.Further,the effectiveness,validity,activeness,and ability to capture the uncertain information,the developed operators are applied to the AI-based Criminal Justice Policy Selection problem.At last,the comparison analysis between prior and proposed studies has been displayed,and then followed by the conclusion of the result.
文摘In this paper,the transferable belief model established on power sets is extended to the permutation event space(PES)and is referred to as the layer-2 transferable belief model.Our goal is to provide a comprehensive approach for handling and modeling uncertainty,capable of representing both quantitative and qualitative information.First,the motivation for proposing the layer-2 transferable belief model and its information processing principles are explored from the perspective of weak propensity.Then,based on these principles,the corresponding information processing methods for the credal and pignistic levels are developed.Finally,the advantages of this model are validated through a classifier that leverages attribute fusion to enhance performance and decision-making accuracy.
基金supported by the National Natural Science Foundation of China(Grant Nos.12020101005,12475202,12347131,and 12405289).
文摘Radio frequency capacitively coupled plasmas(RF CCPs)operated in Ar/O_(2)gas mixtures which are widely adopted in microelectronics,display,and photovoltaic industry,are investigated based on an equivalent circuit model coupled with a global model.This study focuses on the effects of singlet metastable molecule O_(2)(b^(1)∑_(8)^(+)),highly excited Herzberg states O_(2)(A^(3)∑_(u)^(+),A^(3)△_(u),c^(1)∑_(u)^(-)),and the negative ion O_(2)^(-),which are usually neglected in simulation studies.Specifically,their impact on particle densities,electronegativity,electron temperature,voltage drop across the sheath,and absorbed power in the discharge is analyzed.The results indicate that O_(2)(b^(1)∑_(8)^(+))and O_(2)^(-)exhibit relatively high densities in argon-oxygen discharges.While O_(2)(A^(3)∑_(u)^(+),A^(3)△_(u),c^(1)∑_(u)^(-))play a critical role in O_(2)b1S+g production,especially at higher pressure.The inclusion of these particles reduces the electronegativity,electron temperature,and key species densities,especially the O^(-)and O^(*)densities.Moreover,the sheath voltage drop,as well as the inductance and resistance of the plasma bulk are enhanced,while the sheath dissipation power and total absorbed power decrease slightly.With the increasing pressure,the influence of these particles on the discharge properties becomes more significant.The study also explores the generation and loss of main neutral species and charged particles within the pressure range of 20 mTorr-100 mTorr(1 Torr=1.33322×10^(2)Pa),offering insights into essential and non-essential reactions for future low-pressure O_(2)and Ar/O_(2)CCP discharge modeling.
基金supported by the National Key Research and Development Program of China(2018YFB1201500)
文摘This paper uses Gaussian interval type-2 fuzzy se theory on historical traffic volume data processing to obtain a 24-hour prediction of traffic volume with high precision. A K-means clustering method is used in this paper to get 5 minutes traffic volume variation as input data for the Gaussian interval type-2 fuzzy sets which can reflect the distribution of historical traffic volume in one statistical period. Moreover, the cluster with the largest collection of data obtained by K-means clustering method is calculated to get the key parameters of type-2 fuzzy sets, mean and standard deviation of the Gaussian membership function.Using the range of data as the input of Gaussian interval type-2 fuzzy sets leads to the range of traffic volume forecasting output with the ability of describing the possible range of the traffic volume as well as the traffic volume prediction data with high accuracy. The simulation results show that the average relative error is reduced to 8% based on the combined K-means Gaussian interval type-2 fuzzy sets forecasting method. The fluctuation range in terms of an upper and a lower forecasting traffic volume completely envelopes the actual traffic volume and reproduces the fluctuation range of traffic flow.
文摘Objective:To identify alpha-glucosidase inhibitors from Ficus benghalensis and analyze gene set enrichment of regulated protein molecules.Methods:The phytoconstituents of Ficu.s benghalen.sis were queried for inhibitors of alphaglucosidase,also identified as aldose reductase inhibitors.Druglikeness score,absorption,distribution,metabolism,excretion and toxicity profile,biological spectrum,and gene expression were predicated for each compound.Docking study was performed to predict the binding affinity with alpha-glucosidase and aldose reductase and compared with clinically proven molecules.Kyoto Encyclopedia of Genes and Genomes pathway analysis was performed for the regulated genes to identify the modulated pathways.Results:Apigenin,3,4’,5,7-tetrahydroxy-3’-methoxyflavone,and kaempferol were identified as inhibitors of alpha-glucosidase and aldose reductase.Kaempferol was predicted to possess the highest binding affinity with both targets.The p53 signaling pathway was predicted to modulate the majority of protein molecules in diabetes mellitus.All the alpha-glucosidase inhibitors were also predicted as membrane integrity agonist and anti-mutagenic compounds.Conclusions:The current study indicates alpha-glucosidase inhibitors from Ficus benghale,nsis can act as aldose reductase inhibitors after absorption from the intestinal tract.Furthermore,these phytoconstituents are involved in the regulation of numerous protein molecules and pathways.Hence,the anti-diabetic efficacies of these compounds are due to their action on multiple protein molecules and synergistic effects which should be confirmed by future investigations.
