This paper proposes an emotion judgment system by using an electroencephalogram(EEG)feature concept base with premise of noises included.This method references the word concept association system,which associates one ...This paper proposes an emotion judgment system by using an electroencephalogram(EEG)feature concept base with premise of noises included.This method references the word concept association system,which associates one word with other plural words and decides the relationship between several words.In this proposed emotion judgment system,the source EEG is input and 42 EEG features are constructed by EEG data;the data are then calculated by spectrum analysis and normalization.All 2945 EEG data of 4 emotions in the EEG data emotion knowledge base are calculated by the degree of association for getting the nearest EEG data from the EEG feature concept base constructed by 2844 concepts.From the experiment,the accuracy of the proposed system was 55.9%,which was higher than the support vector machine(SVM)method.As this result,the chain structured feature of the EEG feature concept base and the efficiency by the calculation of degree of association for EEG data help reduce the influence of the noise.展开更多
Developmental and reproductive toxicity(DART)endpoint entails a toxicological assessment of all developmental stages and reproductive cycles of an organism.In silico tools to predict DART will provide a method to asse...Developmental and reproductive toxicity(DART)endpoint entails a toxicological assessment of all developmental stages and reproductive cycles of an organism.In silico tools to predict DART will provide a method to assess this complex toxicity endpoint and will be valuable for screening emerging pollutants as well as for m anaging new chemicals in China.Currently,there are few published DART prediction models in China,but many related research and development projects are in progress.In 2013,WU et al.published an expert rule-based DART decision tree(DT).This DT relies on known chemical structures linked to DART to forecast DART potential of a given chemical.Within this procedure,an accurate DART data interpretation is the foundation of building and expanding the DT.This paper excerpted case studies demonstrating DART data curation and interpretation of four chemicals(including 8-hydroxyquinoline,3,5,6-trichloro-2-pyridinol,thiacloprid,and imidacloprid)to expand the existing DART DT.Chemicals were first selected from the database of Solid Waste and Chemicals Management Center,Ministry of Ecology and Environment(MEESCC)in China.The structures of these 4 chemicals were analyzed and preliminarily grouped by chemists based on core structural features,functional groups,receptor binding property,metabolism,and possible mode of actions.Then,the DART conclusion was derived by collecting chemical information,searching,integrating,and interpreting DART data by the toxicologists.Finally,these chemicals were classified into either an existing category or a new category via integrating their chemical features,DART conclusions,and biological properties.The results showed that 8-hydroxyquinoline impacted estrous cyclicity,s exual organ weights,and embryonal development,and 3,5,6-trichloro-2-pyridinol caused central nervous system(CNS)malformations,which were added to an existing subcategory 8e(aromatic compounds with multi-halogen and nitro groups)of the DT.Thiacloprid caused dystocia and fetal skeletal malformation,and imidacloprid disrupted the endocrine system and male fertility.They both contain 2-chloro-5-methylpyridine substituted imidazolidine c yclic ring,which were expected to create a new category of neonicotinoids.The current work delineates a t ransparent process of curating toxicological data for the purpose of DART data interpretation.In the presence of sufficient related structures and DART data,the DT can be expanded by iteratively adding chemicals within the a pplicable domain of each category or subcategory.This DT can potentially serve as a tool for screening emerging pollutants and assessing new chemicals in China.展开更多
Advancements in Natural Language Processing and Deep Learning techniques have significantly pro-pelled the automation of Legal Judgment Prediction,achieving remarkable progress in legal research.Most of the existing r...Advancements in Natural Language Processing and Deep Learning techniques have significantly pro-pelled the automation of Legal Judgment Prediction,achieving remarkable progress in legal research.Most of the existing research works on Legal Judgment Prediction(LJP)use traditional optimization algorithms in deep learning techniques falling into local optimization.This research article focuses on using the modified Pelican Optimization method which mimics the collective behavior of Pelicans in the exploration and exploitation phase during cooperative food searching.Typically,the selection of search agents within a boundary is done randomly,which increases the time required to achieve global optimization.To address this,the proposed Chaotic Opposition Learning-based Pelican Optimization(COLPO)method incorporates the concept of Opposition-Based Learning combined with a chaotic cubic function,enabling deterministic selection of random numbers and reducing the number of iterations needed to reach global optimization.Also,the LJP approach in this work uses improved semantic similarity and entropy features to train a hybrid classifier combining Bi-GRU and Deep Maxout.The output scores are fused using improved score level fusion to boost prediction accuracy.The proposed COLPO method experiments with real-time Madras High Court criminal cases(Dataset 1)and the Supreme Court of India database(Dataset 2),and its performance is compared with nature-inspired algorithms such as Sparrow Search Algorithm(SSA),COOT,Spider Monkey Optimization(SMO),Pelican Optimization Algorithm(POA),as well as baseline classifier models and transformer neural networks.The results show that the proposed hybrid classifier with COLPO outperforms other cutting-edge LJP algorithms achieving 93.4%and 94.24%accuracy,respectively.展开更多
A method of accuracy assignment based on fuzzy comprehensive judgment method (FCJM) in tank fire control system is proposed. From the flowing route of the error sources and their respective correlative signals, the tr...A method of accuracy assignment based on fuzzy comprehensive judgment method (FCJM) in tank fire control system is proposed. From the flowing route of the error sources and their respective correlative signals, the transfer functions of several sources are analysed by means of mathematic simulation, and FCJM is applied to obtain the cost comprehensive factor for each part of system, combining its error sensitivity factor the mathematical model is built to solve the accuracy assignment problem. Simulation result shows the proposed method can help designer of tank fire control system work out an optimal system more efficiently and more economically.展开更多
This article proposes a dual system cognitive reasoning model to enhance audit judgment and decision making. The model is built on the fact that the total cognitive capacity of an individual comprises two systems of r...This article proposes a dual system cognitive reasoning model to enhance audit judgment and decision making. The model is built on the fact that the total cognitive capacity of an individual comprises two systems of reasoning--System 1 that is unconscious, associative, implicit, more emotional and less controlled, and so forth; and System 2 that is conscious, explicit, deliberate and rule-governed, and so forth. The benefits of the proposed model that integrates these two complementary and compensatory systems are first illustrated with an example in audit planning, and second explained how the model could overcome the deficiencies of heuristics specifically in an audit context.展开更多
In order to improve the quality of the judgment documents, the state and government have introduced laws and regulations. However, the current status of trials in our country is that the number of cases is very large....In order to improve the quality of the judgment documents, the state and government have introduced laws and regulations. However, the current status of trials in our country is that the number of cases is very large. Using system to verify the documents can reduce the burden on the judges and ensure the accuracy of the judgment. This paper describes an evaluation system for reasoning description of judgment documents. The main evaluation steps include: segmenting the front and back of the law;extracting the key information in the document by using XML parsing technology;constructing the legal exclusive stop word library and preprocessing inputting text;entering the text input into the model to get the text matching result;using the “match keyword, compare sentencing degree” idea to judge whether the logic is consistent if it is the evaluation of “law and conclusion”;integrating the calculation results of each evaluation subject and feeding clear and concise results back to the system user. Simulation of real application scenarios was conducted to test whether the reasoning lacks key links or is insufficient or the judgment result is unreasonable. The result show that evaluation speed of each document is relatively fast and the accuracy of the evaluation of the common nine criminal cases is high.展开更多
A Dream of Red Mansions is an ancient Chinese chapter-length fictional novel and the first of the Four Great Classical Novels of China. The judgments of the major characters within the book have been studied by many e...A Dream of Red Mansions is an ancient Chinese chapter-length fictional novel and the first of the Four Great Classical Novels of China. The judgments of the major characters within the book have been studied by many experts. The purpose of this paper is to analyse the translation strategies and their effects adopted by different translators for distinct translation purposes by comparing varied translations of the judgments and some of the allusions within them in the two English translations, Yang Xianyi and Hawkes.展开更多
Perhaps the greatest compliment that an attending surgeon can bestow on a resident in training,is to comment,“He/she has good hands.”However,what defines good hands?What parameters are used to make that judgment?As ...Perhaps the greatest compliment that an attending surgeon can bestow on a resident in training,is to comment,“He/she has good hands.”However,what defines good hands?What parameters are used to make that judgment?As an academic urologist,I had the opportunity to observe urology and general surgery residents in the operating room over several decades.展开更多
In this study,terrestrial laser scanning(TLS)is used to collect building data after the M_(s) 7.0 magnitude earthquake in Lushan,Sichuan,China in 2013 for analysis and research.The analysis focuses on extracting the t...In this study,terrestrial laser scanning(TLS)is used to collect building data after the M_(s) 7.0 magnitude earthquake in Lushan,Sichuan,China in 2013 for analysis and research.The analysis focuses on extracting the tilt and deformation of masonry buildings that are difficult to identify through visual inspection in basically intact,slightly damaged and moderately damaged masonry buildings,to solve the problem of ambiguous identification of damage.A quantitative analysis of the determination indexes of the degree of earthquake damage was carried out,and the numerical characteristics parameters such as the curvature of the wall point cloud proximity,angle,contour of the fitted plane of the point cloud,verticality(flatness)of the wall,standard deviation of the profile and angle of the profile were established to determine the degree of earthquake damage to buildings based on LiDAR data.The development of quantitative determination indexes for the degree of earthquake damage of buildings in this study has important application value for LiDAR data in the identification and extraction of earthquake damage information and damage level determination.展开更多
The level set method(LSM)is renowned for producing smooth boundaries and clear geometric representations,facilitating integration with CAD environments.However,its inability to autonomously generate new holes during o...The level set method(LSM)is renowned for producing smooth boundaries and clear geometric representations,facilitating integration with CAD environments.However,its inability to autonomously generate new holes during optimization makes the results highly dependent on the initial design.Although topological derivatives are often introduced to enable hole nucleation,their conversion into effective shape derivatives remains challenging,limiting topological evolution.To address this,a level set topology optimization method with autonomous hole formation(LSM-AHF)is proposed,integrating the material removal mechanism of the SIMP(Solid Isotropic Material with Penalization)method into the LSM framework.First,an initial structure is generated by adjusting the judgment threshold,and a binary thresholding algorithm is subsequently employed to obtain a clear and well-defined geometry.The structural boundaries of this geometry are then identified and used to construct a signed distance field,which serves as the initial level set function.To ensure smooth transitions across material interfaces and enhance numerical stability,Gaussian filtering is subsequently applied to the distance field.Numerical results demonstrate that LSMAHF effectively enables hole nucleation without manual initialization and improves topology change,addressing the respective limitations of conventional LSM and SIMP methods.展开更多
研究发现,人们的道德判断会随季节而变化,而这一现象可能与人们的焦虑水平有关。1 As leaves fall,snow sweeps in or flowers come out,humans change in measurable ways,too.Research suggests a range of psychological phenomena,s...研究发现,人们的道德判断会随季节而变化,而这一现象可能与人们的焦虑水平有关。1 As leaves fall,snow sweeps in or flowers come out,humans change in measurable ways,too.Research suggests a range of psychological phenomena,such as our emotional state,diet and exercise habits,vary throughout the year.Now a new study demonstrates how moral values can also shift with the seasons.展开更多
This study examines how generative artificial intelligence(AI)reshapes creative identity in design education.Drawing on post-humanist and network-based theories,it frames AI as a cognitive collaborator in ideation and...This study examines how generative artificial intelligence(AI)reshapes creative identity in design education.Drawing on post-humanist and network-based theories,it frames AI as a cognitive collaborator in ideation and authorship.Mixed-methods data reveal student anxiety and stylistic confusion,contrasted with designers’adaptive strategies.The AI–Cognition–Identity framework supports curricula that promote reflective,ethical,and epistemically informed AI-integrated pedagogy.展开更多
Carbon fiber reinforced polymer(CFRP)are widely used in various fields because of their high strength,good toughness,and low density.However,owing to their unique forming process,some complex structures such as holes ...Carbon fiber reinforced polymer(CFRP)are widely used in various fields because of their high strength,good toughness,and low density.However,owing to their unique forming process,some complex structures such as holes and grooves cannot be formed directly.Therefore,traditional machining procedures are also required.The drilling process is one of the most common machining methods for CFRP holes,but owing to the complex structure and difficulty in processing CFRP,the quality of the drilling process is often challenging to guarantee.Moreover,the hole-forming defects also have complex forms and lack uniform evaluation indexes.This study summarizes the common orifice defects in the process of CFRP drilling,establishes a comprehensive evaluation method of orifice defects by introducing the relevant theory of the fuzzy complementary judgment matrix,and experimentally verifies the accuracy and reliability of this method.Then,based on the experimental results,a non-linear cutting parameter optimization model is established,which effectively suppresses the orifice defects to ensure the accuracy of the hole size,roundness,and hole wall roughness.The hole-forming quality is subsequently improved.The hole quality evaluation method proposed in this study reduced the dimension of the evaluation index to ensure relevance and effectiveness and improved the convenience of quality inspection and parameter optimization in actual production.展开更多
基金supported by Japan Society for the Promotion of Science(JSPS,16K00311).
文摘This paper proposes an emotion judgment system by using an electroencephalogram(EEG)feature concept base with premise of noises included.This method references the word concept association system,which associates one word with other plural words and decides the relationship between several words.In this proposed emotion judgment system,the source EEG is input and 42 EEG features are constructed by EEG data;the data are then calculated by spectrum analysis and normalization.All 2945 EEG data of 4 emotions in the EEG data emotion knowledge base are calculated by the degree of association for getting the nearest EEG data from the EEG feature concept base constructed by 2844 concepts.From the experiment,the accuracy of the proposed system was 55.9%,which was higher than the support vector machine(SVM)method.As this result,the chain structured feature of the EEG feature concept base and the efficiency by the calculation of degree of association for EEG data help reduce the influence of the noise.
文摘Developmental and reproductive toxicity(DART)endpoint entails a toxicological assessment of all developmental stages and reproductive cycles of an organism.In silico tools to predict DART will provide a method to assess this complex toxicity endpoint and will be valuable for screening emerging pollutants as well as for m anaging new chemicals in China.Currently,there are few published DART prediction models in China,but many related research and development projects are in progress.In 2013,WU et al.published an expert rule-based DART decision tree(DT).This DT relies on known chemical structures linked to DART to forecast DART potential of a given chemical.Within this procedure,an accurate DART data interpretation is the foundation of building and expanding the DT.This paper excerpted case studies demonstrating DART data curation and interpretation of four chemicals(including 8-hydroxyquinoline,3,5,6-trichloro-2-pyridinol,thiacloprid,and imidacloprid)to expand the existing DART DT.Chemicals were first selected from the database of Solid Waste and Chemicals Management Center,Ministry of Ecology and Environment(MEESCC)in China.The structures of these 4 chemicals were analyzed and preliminarily grouped by chemists based on core structural features,functional groups,receptor binding property,metabolism,and possible mode of actions.Then,the DART conclusion was derived by collecting chemical information,searching,integrating,and interpreting DART data by the toxicologists.Finally,these chemicals were classified into either an existing category or a new category via integrating their chemical features,DART conclusions,and biological properties.The results showed that 8-hydroxyquinoline impacted estrous cyclicity,s exual organ weights,and embryonal development,and 3,5,6-trichloro-2-pyridinol caused central nervous system(CNS)malformations,which were added to an existing subcategory 8e(aromatic compounds with multi-halogen and nitro groups)of the DT.Thiacloprid caused dystocia and fetal skeletal malformation,and imidacloprid disrupted the endocrine system and male fertility.They both contain 2-chloro-5-methylpyridine substituted imidazolidine c yclic ring,which were expected to create a new category of neonicotinoids.The current work delineates a t ransparent process of curating toxicological data for the purpose of DART data interpretation.In the presence of sufficient related structures and DART data,the DT can be expanded by iteratively adding chemicals within the a pplicable domain of each category or subcategory.This DT can potentially serve as a tool for screening emerging pollutants and assessing new chemicals in China.
文摘Advancements in Natural Language Processing and Deep Learning techniques have significantly pro-pelled the automation of Legal Judgment Prediction,achieving remarkable progress in legal research.Most of the existing research works on Legal Judgment Prediction(LJP)use traditional optimization algorithms in deep learning techniques falling into local optimization.This research article focuses on using the modified Pelican Optimization method which mimics the collective behavior of Pelicans in the exploration and exploitation phase during cooperative food searching.Typically,the selection of search agents within a boundary is done randomly,which increases the time required to achieve global optimization.To address this,the proposed Chaotic Opposition Learning-based Pelican Optimization(COLPO)method incorporates the concept of Opposition-Based Learning combined with a chaotic cubic function,enabling deterministic selection of random numbers and reducing the number of iterations needed to reach global optimization.Also,the LJP approach in this work uses improved semantic similarity and entropy features to train a hybrid classifier combining Bi-GRU and Deep Maxout.The output scores are fused using improved score level fusion to boost prediction accuracy.The proposed COLPO method experiments with real-time Madras High Court criminal cases(Dataset 1)and the Supreme Court of India database(Dataset 2),and its performance is compared with nature-inspired algorithms such as Sparrow Search Algorithm(SSA),COOT,Spider Monkey Optimization(SMO),Pelican Optimization Algorithm(POA),as well as baseline classifier models and transformer neural networks.The results show that the proposed hybrid classifier with COLPO outperforms other cutting-edge LJP algorithms achieving 93.4%and 94.24%accuracy,respectively.
文摘A method of accuracy assignment based on fuzzy comprehensive judgment method (FCJM) in tank fire control system is proposed. From the flowing route of the error sources and their respective correlative signals, the transfer functions of several sources are analysed by means of mathematic simulation, and FCJM is applied to obtain the cost comprehensive factor for each part of system, combining its error sensitivity factor the mathematical model is built to solve the accuracy assignment problem. Simulation result shows the proposed method can help designer of tank fire control system work out an optimal system more efficiently and more economically.
文摘This article proposes a dual system cognitive reasoning model to enhance audit judgment and decision making. The model is built on the fact that the total cognitive capacity of an individual comprises two systems of reasoning--System 1 that is unconscious, associative, implicit, more emotional and less controlled, and so forth; and System 2 that is conscious, explicit, deliberate and rule-governed, and so forth. The benefits of the proposed model that integrates these two complementary and compensatory systems are first illustrated with an example in audit planning, and second explained how the model could overcome the deficiencies of heuristics specifically in an audit context.
文摘In order to improve the quality of the judgment documents, the state and government have introduced laws and regulations. However, the current status of trials in our country is that the number of cases is very large. Using system to verify the documents can reduce the burden on the judges and ensure the accuracy of the judgment. This paper describes an evaluation system for reasoning description of judgment documents. The main evaluation steps include: segmenting the front and back of the law;extracting the key information in the document by using XML parsing technology;constructing the legal exclusive stop word library and preprocessing inputting text;entering the text input into the model to get the text matching result;using the “match keyword, compare sentencing degree” idea to judge whether the logic is consistent if it is the evaluation of “law and conclusion”;integrating the calculation results of each evaluation subject and feeding clear and concise results back to the system user. Simulation of real application scenarios was conducted to test whether the reasoning lacks key links or is insufficient or the judgment result is unreasonable. The result show that evaluation speed of each document is relatively fast and the accuracy of the evaluation of the common nine criminal cases is high.
文摘A Dream of Red Mansions is an ancient Chinese chapter-length fictional novel and the first of the Four Great Classical Novels of China. The judgments of the major characters within the book have been studied by many experts. The purpose of this paper is to analyse the translation strategies and their effects adopted by different translators for distinct translation purposes by comparing varied translations of the judgments and some of the allusions within them in the two English translations, Yang Xianyi and Hawkes.
文摘Perhaps the greatest compliment that an attending surgeon can bestow on a resident in training,is to comment,“He/she has good hands.”However,what defines good hands?What parameters are used to make that judgment?As an academic urologist,I had the opportunity to observe urology and general surgery residents in the operating room over several decades.
基金Earthquake Science and Technology Program of Hebei Province under Grant Nos.DZ2021120300001,DZ2024083000001,DZ2024112400016 and DZ2025092800001。
文摘In this study,terrestrial laser scanning(TLS)is used to collect building data after the M_(s) 7.0 magnitude earthquake in Lushan,Sichuan,China in 2013 for analysis and research.The analysis focuses on extracting the tilt and deformation of masonry buildings that are difficult to identify through visual inspection in basically intact,slightly damaged and moderately damaged masonry buildings,to solve the problem of ambiguous identification of damage.A quantitative analysis of the determination indexes of the degree of earthquake damage was carried out,and the numerical characteristics parameters such as the curvature of the wall point cloud proximity,angle,contour of the fitted plane of the point cloud,verticality(flatness)of the wall,standard deviation of the profile and angle of the profile were established to determine the degree of earthquake damage to buildings based on LiDAR data.The development of quantitative determination indexes for the degree of earthquake damage of buildings in this study has important application value for LiDAR data in the identification and extraction of earthquake damage information and damage level determination.
基金supported by the National Natural Science Foundation of China[52475096]Guangxi Natural Science Fund for Distinguished Young Scholars[2025GXNSFFA069009]+2 种基金Bagui Outstanding Youth Program of Guangxi,ChinaNatural Science and Technology Innovation Development Doubling Plan Project of Guangxi University,China[2024BZRC010]Innovation Project of Guangxi Graduate Education,China[YCBZ2025014].
文摘The level set method(LSM)is renowned for producing smooth boundaries and clear geometric representations,facilitating integration with CAD environments.However,its inability to autonomously generate new holes during optimization makes the results highly dependent on the initial design.Although topological derivatives are often introduced to enable hole nucleation,their conversion into effective shape derivatives remains challenging,limiting topological evolution.To address this,a level set topology optimization method with autonomous hole formation(LSM-AHF)is proposed,integrating the material removal mechanism of the SIMP(Solid Isotropic Material with Penalization)method into the LSM framework.First,an initial structure is generated by adjusting the judgment threshold,and a binary thresholding algorithm is subsequently employed to obtain a clear and well-defined geometry.The structural boundaries of this geometry are then identified and used to construct a signed distance field,which serves as the initial level set function.To ensure smooth transitions across material interfaces and enhance numerical stability,Gaussian filtering is subsequently applied to the distance field.Numerical results demonstrate that LSMAHF effectively enables hole nucleation without manual initialization and improves topology change,addressing the respective limitations of conventional LSM and SIMP methods.
文摘研究发现,人们的道德判断会随季节而变化,而这一现象可能与人们的焦虑水平有关。1 As leaves fall,snow sweeps in or flowers come out,humans change in measurable ways,too.Research suggests a range of psychological phenomena,such as our emotional state,diet and exercise habits,vary throughout the year.Now a new study demonstrates how moral values can also shift with the seasons.
文摘This study examines how generative artificial intelligence(AI)reshapes creative identity in design education.Drawing on post-humanist and network-based theories,it frames AI as a cognitive collaborator in ideation and authorship.Mixed-methods data reveal student anxiety and stylistic confusion,contrasted with designers’adaptive strategies.The AI–Cognition–Identity framework supports curricula that promote reflective,ethical,and epistemically informed AI-integrated pedagogy.
基金Supported by National Natural Science Foundation of China(Grant No.51875412)Top Discipline Plan of Shanghai Universities-ClassⅠ。
文摘Carbon fiber reinforced polymer(CFRP)are widely used in various fields because of their high strength,good toughness,and low density.However,owing to their unique forming process,some complex structures such as holes and grooves cannot be formed directly.Therefore,traditional machining procedures are also required.The drilling process is one of the most common machining methods for CFRP holes,but owing to the complex structure and difficulty in processing CFRP,the quality of the drilling process is often challenging to guarantee.Moreover,the hole-forming defects also have complex forms and lack uniform evaluation indexes.This study summarizes the common orifice defects in the process of CFRP drilling,establishes a comprehensive evaluation method of orifice defects by introducing the relevant theory of the fuzzy complementary judgment matrix,and experimentally verifies the accuracy and reliability of this method.Then,based on the experimental results,a non-linear cutting parameter optimization model is established,which effectively suppresses the orifice defects to ensure the accuracy of the hole size,roundness,and hole wall roughness.The hole-forming quality is subsequently improved.The hole quality evaluation method proposed in this study reduced the dimension of the evaluation index to ensure relevance and effectiveness and improved the convenience of quality inspection and parameter optimization in actual production.
