Karyotype prescription is based on clinical signs (or reasons for karyotype prescription) which are phenotypic manifestations associated with chromosomal abnormalities. The aim of this study was to establish a corresp...Karyotype prescription is based on clinical signs (or reasons for karyotype prescription) which are phenotypic manifestations associated with chromosomal abnormalities. The aim of this study was to establish a correspondence between karyotype indications and their results in patients. This was a retrospective study that was carried out in the Histology-Embryology-Cytogenetics laboratory of the University Hospital of Cocody-Abidjan from 2014 to 2019. 58 patient files were identified and included the indication or reason for prescribing a constitutional karyotype and the biological result obtained. An individual data sheet was used to collect the data. 17 reasons for prescription were identified and divided into 2 groups. Sexual ambiguity was the most frequent reason (29.3%). The first group (G1) represented the 10 reasons for which the karyotype results were normal. The second group (G2) corresponded of the 7 motives with normal or abnormal karyotype results. Several anomalies were listed according to these reasons: inversions, mosaics (anomalies of number and structure) and trisomy 21. The last was the most frequent chromosomal anomaly (69.24%). It was found in several reasons for karyotype prescription: malformations, neurological disorders, suspected trisomy and cardiac pathology. Several factors could explain these results, among which are the limits of the karyotype and the non-genetic causes that can induce these abnormal phenotypes. Complementary examinations to the karyotype are molecular cytogenetic techniques, notably fluorescence in situ hybridization (FISH) and array comparative genomic hybridization (Array-CGH).展开更多
Tropical cyclones(TC)are often associated with severe weather conditions which cause great losses to lives and property.The precise classification of cyclone tracks is significantly important in thefield of weather fo...Tropical cyclones(TC)are often associated with severe weather conditions which cause great losses to lives and property.The precise classification of cyclone tracks is significantly important in thefield of weather forecasting.In this paper we propose a novel hybrid model that integrates ontology and Support Vector Machine(SVM)to classify the tropical cyclone tracks into four types of classes namely straight,quasi-straight,curving and sinuous based on the track shape.Tropical Cyclone TRacks Ontology(TCTRO)described in this paper is a knowledge base which comprises of classes,objects and data properties that represent the interaction among the TC characteristics.A set of SWRL(Semantic Web Rule Language)rules are directly inserted to the TCTRO ontology for reasoning and inferring new knowledge from ontology.Furthermore,we propose a learning algorithm which utilizes the inferred knowledge for optimizing the feature subset.According to experiments on the IBTrACS dataset,the proposed ontology based SVM classifier achieves an accuracy of 98.3%with reduced classification error rates.展开更多
In Chinese medicine, practitioners assess patients’ complaints, analyze their underlying problems, identify causes and come to a diagnosis, which then directs treatment. What is not obvious and not recorded in a cons...In Chinese medicine, practitioners assess patients’ complaints, analyze their underlying problems, identify causes and come to a diagnosis, which then directs treatment. What is not obvious and not recorded in a consultation is the clinical reasoning process that practitioners use. The research filmed three practitioners in the UK while they conducted a consultation and treatment on new patients. The practitioners and researchers viewed the films and used them as aide-memoirs while the reasoning process throughout was discussed. In order to determine the pattern, practitioners used the four examinations to gather information from the patient in an iterative process;their aesthetic reasoning was highly developed. Through triangulation they checked the information they received against a detailed understanding of the qi-dynamic. They used highly analytical strategies of forward(inductive) and backward(deductive) reasoning against the prototypes of the signs and symptoms that indicate a specific Zheng. This was achieved through an abductive process that linked description with explanation and causal factors with pathological mechanisms. The feedback loop with the patient continued through the consultation and into the treatment. A process of translation and interpretation was needed to turn the patient’s story into the practitioner’s story of qi-dynamics that then directed the treatment. Awareness of our clinical reasoning process will mitigate against biases, improve our diagnoses and treatment choices and support the training of students.展开更多
Due to the structural dependencies among concurrent events in the knowledge graph and the substantial amount of sequential correlation information carried by temporally adjacent events,we propose an Independent Recurr...Due to the structural dependencies among concurrent events in the knowledge graph and the substantial amount of sequential correlation information carried by temporally adjacent events,we propose an Independent Recurrent Temporal Graph Convolution Networks(IndRT-GCNets)framework to efficiently and accurately capture event attribute information.The framework models the knowledge graph sequences to learn the evolutionary represen-tations of entities and relations within each period.Firstly,by utilizing the temporal graph convolution module in the evolutionary representation unit,the framework captures the structural dependency relationships within the knowledge graph in each period.Meanwhile,to achieve better event representation and establish effective correlations,an independent recurrent neural network is employed to implement auto-regressive modeling.Furthermore,static attributes of entities in the entity-relation events are constrained andmerged using a static graph constraint to obtain optimal entity representations.Finally,the evolution of entity and relation representations is utilized to predict events in the next subsequent step.On multiple real-world datasets such as Freebase13(FB13),Freebase 15k(FB15K),WordNet11(WN11),WordNet18(WN18),FB15K-237,WN18RR,YAGO3-10,and Nell-995,the results of multiple evaluation indicators show that our proposed IndRT-GCNets framework outperforms most existing models on knowledge reasoning tasks,which validates the effectiveness and robustness.展开更多
Similarity has been playing an important role in computer science,artificial intelligence(AI)and data science.However,similarity intelligence has been ignored in these disciplines.Similarity intelligence is a process ...Similarity has been playing an important role in computer science,artificial intelligence(AI)and data science.However,similarity intelligence has been ignored in these disciplines.Similarity intelligence is a process of discovering intelligence through similarity.This article will explore similarity intelligence,similarity-based reasoning,similarity computing and analytics.More specifically,this article looks at the similarity as an intelligence and its impact on a few areas in the real world.It explores similarity intelligence accompanying experience-based intelligence,knowledge-based intelligence,and data-based intelligence to play an important role in computer science,AI,and data science.This article explores similarity-based reasoning(SBR)and proposes three similarity-based inference rules.It then examines similarity computing and analytics,and a multiagent SBR system.The main contributions of this article are:1)Similarity intelligence is discovered from experience-based intelligence consisting of data-based intelligence and knowledge-based intelligence.2)Similarity-based reasoning,computing and analytics can be used to create similarity intelligence.The proposed approach will facilitate research and development of similarity intelligence,similarity computing and analytics,machine learning and case-based reasoning.展开更多
The model for protection of personal information dis-closed according to the law has changed from indirect protection to direct protection.The indirect protection model for traditional repu-tation rights and privacy r...The model for protection of personal information dis-closed according to the law has changed from indirect protection to direct protection.The indirect protection model for traditional repu-tation rights and privacy rights was not enough to meet the practical needs of governance.However;due to the ambiguity in the application of the“reasonable”processing requirements,the direct protection model centered on Article 27 of the Personal Information Protection Law also is not enough to effectively respond to practical disputes.The essence of the problem is to resolve the tension between informa-tion circulation and risk control and reshape the legal order for the protection of personal information disclosed according to the law.The determination of“reasonable”should be centered on the scenario theory and holism interpretation and carried out by using the interpre-tation technique of the dynamic system under Article 998 of the Civil Code.With the support of scenario-based discussions and comparative propositions,the crawling and tag extraction of personal information.disclosed according to the law should be considered as reasonable processing;profiling and automated decision-making should not be covered in the scope of reasonable processing,in principle;for behav-iors such as correlation analysis,elements like information subject,identifiability and sensitivity should be comprehensively considered to draw open and inclusive conclusions in individual cases.展开更多
TEFL in Thailand is still not successful compared with other countries in Asia.On the basis of literature and study of the relevant official documents,the present paper makes an analysis on the reasons for the failure...TEFL in Thailand is still not successful compared with other countries in Asia.On the basis of literature and study of the relevant official documents,the present paper makes an analysis on the reasons for the failure of TEFL in Thailand.It is revealed that the main reason for the failure of TEFL in Thailand is lack of qualified teachers.Some solutions to the failure of TEFL are also proposed in the paper.展开更多
All social phenomena are,to some extent,determined by economy,and language is also under the leverage of economic factor.With the development of society,economy,science and economy,human interpretation and consciousne...All social phenomena are,to some extent,determined by economy,and language is also under the leverage of economic factor.With the development of society,economy,science and economy,human interpretation and consciousness of their language have been greatly enhanced.The exploration of catchword can be developed from its definition,its characteristics and reasons for its emergence.展开更多
This paper compared the difference between the traditional Petri nets and reasoning Petri nets(RPN),and presented a fuzzy reasoning Petri net(FRPN) model to represent the fuzzy production rules of a rule based system....This paper compared the difference between the traditional Petri nets and reasoning Petri nets(RPN),and presented a fuzzy reasoning Petri net(FRPN) model to represent the fuzzy production rules of a rule based system.Based on the FRPN model,a formal reasoning algorithm using the operators in max algebra was proposed to perform fuzzy reasoning automatically.The algorithm is consistent with the matrix equation expression method in the traditional Petri net.Its legitimacy and feasibility were testified through an example.展开更多
Wetlands are ecosystems with many f unctions.But the general public and government lack a comprehen-sive understanding of the importance of wetland benefits,thus making bl indly exploitation,wetland resour ces decreas...Wetlands are ecosystems with many f unctions.But the general public and government lack a comprehen-sive understanding of the importance of wetland benefits,thus making bl indly exploitation,wetland resour ces decreasing and losing biodiversity.So wetlands in China,as in most countries,have suffered heavily from the pressure o f develop-ment and have confronted with the thr eats of loss.The paper takes Sanjian g Plain marshes,lakes in the middle r eaches of the Changjiang(Yangtze)River,coastal wetlands and mangroves as cases to study wetland loss in China,and puts forward main existing reasons of wetland loss,such as blindly reclamati on and exploitation of wetland resou rces,over-exploitation of bio-resource s in wetland,etc.More recently,there has been a growing recognition of t he benefits of wetlands and a wide range of legal and regulatory initiatives have been undertaken which are designed to impro ve wetland management and conservation.On the basis of the above analysis,the paper brings forward some suggestions on wetland conservation.展开更多
The problem of fault reasoning has aroused great concern in scientific and engineering fields.However,fault investigation and reasoning of complex system is not a simple reasoning decision-making problem.It has become...The problem of fault reasoning has aroused great concern in scientific and engineering fields.However,fault investigation and reasoning of complex system is not a simple reasoning decision-making problem.It has become a typical multi-constraint and multi-objective reticulate optimization decision-making problem under many influencing factors and constraints.So far,little research has been carried out in this field.This paper transforms the fault reasoning problem of complex system into a paths-searching problem starting from known symptoms to fault causes.Three optimization objectives are considered simultaneously: maximum probability of average fault,maximum average importance,and minimum average complexity of test.Under the constraints of both known symptoms and the causal relationship among different components,a multi-objective optimization mathematical model is set up,taking minimizing cost of fault reasoning as the target function.Since the problem is non-deterministic polynomial-hard(NP-hard),a modified multi-objective ant colony algorithm is proposed,in which a reachability matrix is set up to constrain the feasible search nodes of the ants and a new pseudo-random-proportional rule and a pheromone adjustment mechinism are constructed to balance conflicts between the optimization objectives.At last,a Pareto optimal set is acquired.Evaluation functions based on validity and tendency of reasoning paths are defined to optimize noninferior set,through which the final fault causes can be identified according to decision-making demands,thus realize fault reasoning of the multi-constraint and multi-objective complex system.Reasoning results demonstrate that the improved multi-objective ant colony optimization(IMACO) can realize reasoning and locating fault positions precisely by solving the multi-objective fault diagnosis model,which provides a new method to solve the problem of multi-constraint and multi-objective fault diagnosis and reasoning of complex system.展开更多
The knowledge graph(KG) that represents structural relations among entities has become an increasingly important research field for knowledge-driven artificial intelligence. In this survey, a comprehensive review of K...The knowledge graph(KG) that represents structural relations among entities has become an increasingly important research field for knowledge-driven artificial intelligence. In this survey, a comprehensive review of KG and KG reasoning is provided. It introduces an overview of KGs, including representation, storage, and essential technologies. Specifically, it summarizes several types of knowledge reasoning approaches, including logic rules-based, representation-based, and neural network-based methods. Moreover, this paper analyzes the representation methods of knowledge hypergraphs. To effectively model hyper-relational data and improve the performance of knowledge reasoning, a three-layer knowledge hypergraph model is proposed. Finally, it analyzes the advantages of three-layer knowledge hypergraphs through reasoning and update algorithms which could facilitate future research.展开更多
Slope is a non-linear and uncertain kinetic system affected by many factors. In view of the incompleteness and uncertainty of the information of slope stability evaluation, a new method of slope stability eralu-ation ...Slope is a non-linear and uncertain kinetic system affected by many factors. In view of the incompleteness and uncertainty of the information of slope stability evaluation, a new method of slope stability eralu-ation by using case-based reasoning is presented. Considering the sensitivity of attribute iveights to the environment , the algorithm of attribute iveights is set up on the basis of the concept of changeable weights . Calculating the similarity between target case of the slope and base case, the stability of target case is evaluated. It is shown from examples that the method is simple, visual, practical, and convenient for use .展开更多
Multimorbidity, defined as 2 or more chronic diseases, is of increasing importance for health professionals. Many factors are at play when it comes to multimorbidity, but we still know very little about how clinicians...Multimorbidity, defined as 2 or more chronic diseases, is of increasing importance for health professionals. Many factors are at play when it comes to multimorbidity, but we still know very little about how clinicians actually weigh up the different factors—medical, social, and psychological—to reach a particular course of action. Further research is therefore required to explore the ways in which clinical reasoning processes are involved in the follow up of patients suffering from multimorbidities, to highlight their potential risks of errors. A better understanding of these clinical processes will also enrich supervision of trainees and collaboration between healthcare professionals involved in primary care.展开更多
Natural language processing(NLP)is a subfield of artificial intelligence that focuses on enabling computers to understand and process human languages.In the last five years,we have witnessed the rapid development of N...Natural language processing(NLP)is a subfield of artificial intelligence that focuses on enabling computers to understand and process human languages.In the last five years,we have witnessed the rapid development of NLP in tasks such as machine translation,question-answering,and machine reading comprehension based on deep learning and an enormous volume of annotated and unannotated data.In this paper,we will review the latest progress in the neural network-based NLP framework(neural NLP)from three perspectives:modeling,learning,and reasoning.In the modeling section,we will describe several fundamental neural network-based modeling paradigms,such as word embedding,sentence embedding,and sequence-to-sequence modeling,which are widely used in modern NLP engines.In the learning section,we will introduce widely used learning methods for NLP models,including supervised,semi-supervised,and unsupervised learning;multitask learning;transfer learning;and active learning.We view reasoning as a new and exciting direction for neural NLP,but it has yet to be well addressed.In the reasoning section,we will review reasoning mechanisms,including the knowledge,existing non-neural inference methods,and new neural inference methods.We emphasize the importance of reasoning in this paper because it is important for building interpretable and knowledgedriven neural NLP models to handle complex tasks.At the end of this paper,we will briefly outline our thoughts on the future directions of neural NLP.展开更多
AIM To investigate factors predicting treatment completion and treatment outcome of the Reasoning and Rehabilitation Mental Health Programme(R&R2MHP) cognitive skills programme for mentally disordered offenders. M...AIM To investigate factors predicting treatment completion and treatment outcome of the Reasoning and Rehabilitation Mental Health Programme(R&R2MHP) cognitive skills programme for mentally disordered offenders. METHODS Secondary analysis of data previously obtained from 97 male patients who were sectioned and detained under the United Kingdom Mental Health Act in low, medium and high security hospitals and who had completed R&R2MHP. Predictors of treatment completion included background variables and five outcome measures: Four self-reported measures of violent attitudes, social problem-solving skills, reactive anger and locus of control and an objective measure of behaviour on theward that was completed by staff. Completion of the 16 session programme, which was delivered on a weekly basis, was classified as ≥ 12 sessions.RESULTS It was found that the R&R2MHP is appropriate for delivery to participants of different ages, ethnic background, and at different levels of security without the completion rate or treatment effectiveness being compromised. Participants taking oral typical psychotropic medication were over seven times more likely to complete the programme than other participants. Behavioural disturbance on the ward prior to commencing the programme predicted non-completion(medium effect size). As far as treatment completion was concerned, none of the background factors predicted treatment effectiveness(age, ethnic background, level of security, number of previous convictions and number of previous hospital admissions). The best predictor of treatment effectiveness was attitude towards violence suggesting that this should be the primary outcome measure in future research evaluating outcomes of the R&R2MHP cognitive skills program. CONCLUSION The findings suggest that a stable mental state is a key factor that predicts treatment completion.展开更多
Extracting and synthesizing information from existing and massive amounts of geology spatial data sets is of great scientific significance and has considerable value in its applications. To make mineral exploration le...Extracting and synthesizing information from existing and massive amounts of geology spatial data sets is of great scientific significance and has considerable value in its applications. To make mineral exploration less expensive, more efficient, and more accurate, it is important to move beyond traditional concepts and establish a rapid, efficient, and intelligent method of predicting the existence and location of minerals. This paper describes a case-based reasoning (CBR) method for mineral prospectivity mapping that takes spatial features of geology data into account and offers an intelligent approach. This method include a metallogenic case representation that combines spatial and attribute features, metallogenic case-based storage organization, and a metallogenic case similarity retrieval model. The experiments were performed in the eastern Kunlun Mountains, China using CBR and weights-of-evidence (WOE), respectively. The results show that the prediction accuracy of the CBR is higher than that of the WOE.展开更多
College English teaching has been regarded as time- consuming with low efficiency for a long time. This thesis proceeds with the entity of English education in China, deals with the main problems lying in the current ...College English teaching has been regarded as time- consuming with low efficiency for a long time. This thesis proceeds with the entity of English education in China, deals with the main problems lying in the current college English teaching from 3 perspectives, including the nation and society, teachers, and students, and provides 5 suggestions accordingly.展开更多
文摘Karyotype prescription is based on clinical signs (or reasons for karyotype prescription) which are phenotypic manifestations associated with chromosomal abnormalities. The aim of this study was to establish a correspondence between karyotype indications and their results in patients. This was a retrospective study that was carried out in the Histology-Embryology-Cytogenetics laboratory of the University Hospital of Cocody-Abidjan from 2014 to 2019. 58 patient files were identified and included the indication or reason for prescribing a constitutional karyotype and the biological result obtained. An individual data sheet was used to collect the data. 17 reasons for prescription were identified and divided into 2 groups. Sexual ambiguity was the most frequent reason (29.3%). The first group (G1) represented the 10 reasons for which the karyotype results were normal. The second group (G2) corresponded of the 7 motives with normal or abnormal karyotype results. Several anomalies were listed according to these reasons: inversions, mosaics (anomalies of number and structure) and trisomy 21. The last was the most frequent chromosomal anomaly (69.24%). It was found in several reasons for karyotype prescription: malformations, neurological disorders, suspected trisomy and cardiac pathology. Several factors could explain these results, among which are the limits of the karyotype and the non-genetic causes that can induce these abnormal phenotypes. Complementary examinations to the karyotype are molecular cytogenetic techniques, notably fluorescence in situ hybridization (FISH) and array comparative genomic hybridization (Array-CGH).
文摘Tropical cyclones(TC)are often associated with severe weather conditions which cause great losses to lives and property.The precise classification of cyclone tracks is significantly important in thefield of weather forecasting.In this paper we propose a novel hybrid model that integrates ontology and Support Vector Machine(SVM)to classify the tropical cyclone tracks into four types of classes namely straight,quasi-straight,curving and sinuous based on the track shape.Tropical Cyclone TRacks Ontology(TCTRO)described in this paper is a knowledge base which comprises of classes,objects and data properties that represent the interaction among the TC characteristics.A set of SWRL(Semantic Web Rule Language)rules are directly inserted to the TCTRO ontology for reasoning and inferring new knowledge from ontology.Furthermore,we propose a learning algorithm which utilizes the inferred knowledge for optimizing the feature subset.According to experiments on the IBTrACS dataset,the proposed ontology based SVM classifier achieves an accuracy of 98.3%with reduced classification error rates.
基金This research was self-funded as part of an Education Doctorate at the Institute of Education,University College London.
文摘In Chinese medicine, practitioners assess patients’ complaints, analyze their underlying problems, identify causes and come to a diagnosis, which then directs treatment. What is not obvious and not recorded in a consultation is the clinical reasoning process that practitioners use. The research filmed three practitioners in the UK while they conducted a consultation and treatment on new patients. The practitioners and researchers viewed the films and used them as aide-memoirs while the reasoning process throughout was discussed. In order to determine the pattern, practitioners used the four examinations to gather information from the patient in an iterative process;their aesthetic reasoning was highly developed. Through triangulation they checked the information they received against a detailed understanding of the qi-dynamic. They used highly analytical strategies of forward(inductive) and backward(deductive) reasoning against the prototypes of the signs and symptoms that indicate a specific Zheng. This was achieved through an abductive process that linked description with explanation and causal factors with pathological mechanisms. The feedback loop with the patient continued through the consultation and into the treatment. A process of translation and interpretation was needed to turn the patient’s story into the practitioner’s story of qi-dynamics that then directed the treatment. Awareness of our clinical reasoning process will mitigate against biases, improve our diagnoses and treatment choices and support the training of students.
基金the National Natural Science Founda-tion of China(62062062)hosted by Gulila Altenbek.
文摘Due to the structural dependencies among concurrent events in the knowledge graph and the substantial amount of sequential correlation information carried by temporally adjacent events,we propose an Independent Recurrent Temporal Graph Convolution Networks(IndRT-GCNets)framework to efficiently and accurately capture event attribute information.The framework models the knowledge graph sequences to learn the evolutionary represen-tations of entities and relations within each period.Firstly,by utilizing the temporal graph convolution module in the evolutionary representation unit,the framework captures the structural dependency relationships within the knowledge graph in each period.Meanwhile,to achieve better event representation and establish effective correlations,an independent recurrent neural network is employed to implement auto-regressive modeling.Furthermore,static attributes of entities in the entity-relation events are constrained andmerged using a static graph constraint to obtain optimal entity representations.Finally,the evolution of entity and relation representations is utilized to predict events in the next subsequent step.On multiple real-world datasets such as Freebase13(FB13),Freebase 15k(FB15K),WordNet11(WN11),WordNet18(WN18),FB15K-237,WN18RR,YAGO3-10,and Nell-995,the results of multiple evaluation indicators show that our proposed IndRT-GCNets framework outperforms most existing models on knowledge reasoning tasks,which validates the effectiveness and robustness.
文摘Similarity has been playing an important role in computer science,artificial intelligence(AI)and data science.However,similarity intelligence has been ignored in these disciplines.Similarity intelligence is a process of discovering intelligence through similarity.This article will explore similarity intelligence,similarity-based reasoning,similarity computing and analytics.More specifically,this article looks at the similarity as an intelligence and its impact on a few areas in the real world.It explores similarity intelligence accompanying experience-based intelligence,knowledge-based intelligence,and data-based intelligence to play an important role in computer science,AI,and data science.This article explores similarity-based reasoning(SBR)and proposes three similarity-based inference rules.It then examines similarity computing and analytics,and a multiagent SBR system.The main contributions of this article are:1)Similarity intelligence is discovered from experience-based intelligence consisting of data-based intelligence and knowledge-based intelligence.2)Similarity-based reasoning,computing and analytics can be used to create similarity intelligence.The proposed approach will facilitate research and development of similarity intelligence,similarity computing and analytics,machine learning and case-based reasoning.
文摘The model for protection of personal information dis-closed according to the law has changed from indirect protection to direct protection.The indirect protection model for traditional repu-tation rights and privacy rights was not enough to meet the practical needs of governance.However;due to the ambiguity in the application of the“reasonable”processing requirements,the direct protection model centered on Article 27 of the Personal Information Protection Law also is not enough to effectively respond to practical disputes.The essence of the problem is to resolve the tension between informa-tion circulation and risk control and reshape the legal order for the protection of personal information disclosed according to the law.The determination of“reasonable”should be centered on the scenario theory and holism interpretation and carried out by using the interpre-tation technique of the dynamic system under Article 998 of the Civil Code.With the support of scenario-based discussions and comparative propositions,the crawling and tag extraction of personal information.disclosed according to the law should be considered as reasonable processing;profiling and automated decision-making should not be covered in the scope of reasonable processing,in principle;for behav-iors such as correlation analysis,elements like information subject,identifiability and sensitivity should be comprehensively considered to draw open and inclusive conclusions in individual cases.
文摘TEFL in Thailand is still not successful compared with other countries in Asia.On the basis of literature and study of the relevant official documents,the present paper makes an analysis on the reasons for the failure of TEFL in Thailand.It is revealed that the main reason for the failure of TEFL in Thailand is lack of qualified teachers.Some solutions to the failure of TEFL are also proposed in the paper.
文摘All social phenomena are,to some extent,determined by economy,and language is also under the leverage of economic factor.With the development of society,economy,science and economy,human interpretation and consciousness of their language have been greatly enhanced.The exploration of catchword can be developed from its definition,its characteristics and reasons for its emergence.
文摘This paper compared the difference between the traditional Petri nets and reasoning Petri nets(RPN),and presented a fuzzy reasoning Petri net(FRPN) model to represent the fuzzy production rules of a rule based system.Based on the FRPN model,a formal reasoning algorithm using the operators in max algebra was proposed to perform fuzzy reasoning automatically.The algorithm is consistent with the matrix equation expression method in the traditional Petri net.Its legitimacy and feasibility were testified through an example.
文摘Wetlands are ecosystems with many f unctions.But the general public and government lack a comprehen-sive understanding of the importance of wetland benefits,thus making bl indly exploitation,wetland resour ces decreasing and losing biodiversity.So wetlands in China,as in most countries,have suffered heavily from the pressure o f develop-ment and have confronted with the thr eats of loss.The paper takes Sanjian g Plain marshes,lakes in the middle r eaches of the Changjiang(Yangtze)River,coastal wetlands and mangroves as cases to study wetland loss in China,and puts forward main existing reasons of wetland loss,such as blindly reclamati on and exploitation of wetland resou rces,over-exploitation of bio-resource s in wetland,etc.More recently,there has been a growing recognition of t he benefits of wetlands and a wide range of legal and regulatory initiatives have been undertaken which are designed to impro ve wetland management and conservation.On the basis of the above analysis,the paper brings forward some suggestions on wetland conservation.
基金supported by Sub-project of Key National Science and Technology Special Project of China(Grant No.2011ZX05056)
文摘The problem of fault reasoning has aroused great concern in scientific and engineering fields.However,fault investigation and reasoning of complex system is not a simple reasoning decision-making problem.It has become a typical multi-constraint and multi-objective reticulate optimization decision-making problem under many influencing factors and constraints.So far,little research has been carried out in this field.This paper transforms the fault reasoning problem of complex system into a paths-searching problem starting from known symptoms to fault causes.Three optimization objectives are considered simultaneously: maximum probability of average fault,maximum average importance,and minimum average complexity of test.Under the constraints of both known symptoms and the causal relationship among different components,a multi-objective optimization mathematical model is set up,taking minimizing cost of fault reasoning as the target function.Since the problem is non-deterministic polynomial-hard(NP-hard),a modified multi-objective ant colony algorithm is proposed,in which a reachability matrix is set up to constrain the feasible search nodes of the ants and a new pseudo-random-proportional rule and a pheromone adjustment mechinism are constructed to balance conflicts between the optimization objectives.At last,a Pareto optimal set is acquired.Evaluation functions based on validity and tendency of reasoning paths are defined to optimize noninferior set,through which the final fault causes can be identified according to decision-making demands,thus realize fault reasoning of the multi-constraint and multi-objective complex system.Reasoning results demonstrate that the improved multi-objective ant colony optimization(IMACO) can realize reasoning and locating fault positions precisely by solving the multi-objective fault diagnosis model,which provides a new method to solve the problem of multi-constraint and multi-objective fault diagnosis and reasoning of complex system.
基金supported by the Key Science and Technology R&D Project of Sichuan Province under Grants No. 2022YFG0038 and No. 2021YFG0018
文摘The knowledge graph(KG) that represents structural relations among entities has become an increasingly important research field for knowledge-driven artificial intelligence. In this survey, a comprehensive review of KG and KG reasoning is provided. It introduces an overview of KGs, including representation, storage, and essential technologies. Specifically, it summarizes several types of knowledge reasoning approaches, including logic rules-based, representation-based, and neural network-based methods. Moreover, this paper analyzes the representation methods of knowledge hypergraphs. To effectively model hyper-relational data and improve the performance of knowledge reasoning, a three-layer knowledge hypergraph model is proposed. Finally, it analyzes the advantages of three-layer knowledge hypergraphs through reasoning and update algorithms which could facilitate future research.
基金Funded by Hubei Natural Science Foundation (2000J146)
文摘Slope is a non-linear and uncertain kinetic system affected by many factors. In view of the incompleteness and uncertainty of the information of slope stability evaluation, a new method of slope stability eralu-ation by using case-based reasoning is presented. Considering the sensitivity of attribute iveights to the environment , the algorithm of attribute iveights is set up on the basis of the concept of changeable weights . Calculating the similarity between target case of the slope and base case, the stability of target case is evaluated. It is shown from examples that the method is simple, visual, practical, and convenient for use .
文摘Multimorbidity, defined as 2 or more chronic diseases, is of increasing importance for health professionals. Many factors are at play when it comes to multimorbidity, but we still know very little about how clinicians actually weigh up the different factors—medical, social, and psychological—to reach a particular course of action. Further research is therefore required to explore the ways in which clinical reasoning processes are involved in the follow up of patients suffering from multimorbidities, to highlight their potential risks of errors. A better understanding of these clinical processes will also enrich supervision of trainees and collaboration between healthcare professionals involved in primary care.
文摘Natural language processing(NLP)is a subfield of artificial intelligence that focuses on enabling computers to understand and process human languages.In the last five years,we have witnessed the rapid development of NLP in tasks such as machine translation,question-answering,and machine reading comprehension based on deep learning and an enormous volume of annotated and unannotated data.In this paper,we will review the latest progress in the neural network-based NLP framework(neural NLP)from three perspectives:modeling,learning,and reasoning.In the modeling section,we will describe several fundamental neural network-based modeling paradigms,such as word embedding,sentence embedding,and sequence-to-sequence modeling,which are widely used in modern NLP engines.In the learning section,we will introduce widely used learning methods for NLP models,including supervised,semi-supervised,and unsupervised learning;multitask learning;transfer learning;and active learning.We view reasoning as a new and exciting direction for neural NLP,but it has yet to be well addressed.In the reasoning section,we will review reasoning mechanisms,including the knowledge,existing non-neural inference methods,and new neural inference methods.We emphasize the importance of reasoning in this paper because it is important for building interpretable and knowledgedriven neural NLP models to handle complex tasks.At the end of this paper,we will briefly outline our thoughts on the future directions of neural NLP.
基金supported by the National Institute for Health Research (NIHR) Imperial Biomedical Research Centre
文摘AIM To investigate factors predicting treatment completion and treatment outcome of the Reasoning and Rehabilitation Mental Health Programme(R&R2MHP) cognitive skills programme for mentally disordered offenders. METHODS Secondary analysis of data previously obtained from 97 male patients who were sectioned and detained under the United Kingdom Mental Health Act in low, medium and high security hospitals and who had completed R&R2MHP. Predictors of treatment completion included background variables and five outcome measures: Four self-reported measures of violent attitudes, social problem-solving skills, reactive anger and locus of control and an objective measure of behaviour on theward that was completed by staff. Completion of the 16 session programme, which was delivered on a weekly basis, was classified as ≥ 12 sessions.RESULTS It was found that the R&R2MHP is appropriate for delivery to participants of different ages, ethnic background, and at different levels of security without the completion rate or treatment effectiveness being compromised. Participants taking oral typical psychotropic medication were over seven times more likely to complete the programme than other participants. Behavioural disturbance on the ward prior to commencing the programme predicted non-completion(medium effect size). As far as treatment completion was concerned, none of the background factors predicted treatment effectiveness(age, ethnic background, level of security, number of previous convictions and number of previous hospital admissions). The best predictor of treatment effectiveness was attitude towards violence suggesting that this should be the primary outcome measure in future research evaluating outcomes of the R&R2MHP cognitive skills program. CONCLUSION The findings suggest that a stable mental state is a key factor that predicts treatment completion.
文摘Extracting and synthesizing information from existing and massive amounts of geology spatial data sets is of great scientific significance and has considerable value in its applications. To make mineral exploration less expensive, more efficient, and more accurate, it is important to move beyond traditional concepts and establish a rapid, efficient, and intelligent method of predicting the existence and location of minerals. This paper describes a case-based reasoning (CBR) method for mineral prospectivity mapping that takes spatial features of geology data into account and offers an intelligent approach. This method include a metallogenic case representation that combines spatial and attribute features, metallogenic case-based storage organization, and a metallogenic case similarity retrieval model. The experiments were performed in the eastern Kunlun Mountains, China using CBR and weights-of-evidence (WOE), respectively. The results show that the prediction accuracy of the CBR is higher than that of the WOE.
文摘College English teaching has been regarded as time- consuming with low efficiency for a long time. This thesis proceeds with the entity of English education in China, deals with the main problems lying in the current college English teaching from 3 perspectives, including the nation and society, teachers, and students, and provides 5 suggestions accordingly.
