This paper explores a tree kernel based method for semantic role labeling(SRL)of Chinese nominal predicates via a convolution tree kernel.In particular,a new parse tree representation structure,called dependency-drive...This paper explores a tree kernel based method for semantic role labeling(SRL)of Chinese nominal predicates via a convolution tree kernel.In particular,a new parse tree representation structure,called dependency-driven constituent parse tree(D-CPT),is proposed to combine the advantages of both constituent and dependence parse trees.This is achieved by directly representing various kinds of dependency relations in a CPT-style structure,which employs dependency relation types instead of phrase labels in CPT(Constituent Parse Tree).In this way,D-CPT not only keeps the dependency relationship information in the dependency parse tree(DPT)structure but also retains the basic hierarchical structure of CPT style.Moreover,several schemes are designed to extract various kinds of necessary information,such as the shortest path between the nominal predicate and the argument candidate,the support verb of the nominal predicate and the head argument modified by the argument candidate,from D-CPT.This largely reduces the noisy information inherent in D-CPT.Finally,a convolution tree kernel is employed to compute the similarity between two parse trees.Besides,we also implement a feature-based method based on D-CPT.Evaluation on Chinese NomBank corpus shows that our tree kernel based method on D-CPT performs significantly better than other tree kernel-based ones and achieves comparable performance with the state-of-the-art feature-based ones.This indicates the effectiveness of the novel D-CPT structure in representing various kinds of dependency relations in a CPT-style structure and our tree kernel based method in exploring the novel D-CPT structure.This also illustrates that the kernel-based methods are competitive and they are complementary with the feature-based methods on SRL.展开更多
Frege argued that a predicate was a functional expression and the reference of it a concept, which as a predicative function had one or more empty places and was thus incomplete. Frege's view gives rise to what has b...Frege argued that a predicate was a functional expression and the reference of it a concept, which as a predicative function had one or more empty places and was thus incomplete. Frege's view gives rise to what has been known as the paradox of the concept "horse." In order to resolve this paradox, I argue for an opposite view which retains the point that a predicate is a function, i.e. that a predicative function is complete in a sense. Specifically speaking, a predicate performing the function of a predicate has at least one empty place and has no reference, while a predicate performing the function of a subject does not have any empty place but does have a reference. Frege not only regarded a concept with one or more empty places as the reference of a predicate but also took a set of objects without any empty place to be the extension of a concept with one or more empty places. Thus, it presents a complex relationship between the reference of a predicate and its corresponding extension, leading to disharmony in his theory. I argue that this is because there is a major defect in Frege's theory of meaning, namely the neglect of common names. What he called extensions of concepts are actually extensions of common names, and the references of predicates and the extensions of common names have a substantial difference despite being closely related.展开更多
Code obfuscation is a crucial technique for protecting software against reverse engineering and security attacks.Among various obfuscation methods,opaque predicates,which are recognized as flexible and promising,are w...Code obfuscation is a crucial technique for protecting software against reverse engineering and security attacks.Among various obfuscation methods,opaque predicates,which are recognized as flexible and promising,are widely used to increase control-flow complexity.However,traditional opaque predicates are increasingly vulnerable to Dynamic Symbolic Execution(DSE)attacks,which can efficiently identify and eliminate them.To address this issue,this paper proposes a novel approach for anti-DSE opaque predicates that effectively resists symbolic execution-based deobfuscation.Our method introduces two key techniques:single-way function opaque predicates,which leverage hash functions and logarithmic transformations to prevent constraint solvers from generating feasible inputs,and path-explosion opaque predicates,which generate an excessive number of execution paths,overwhelming symbolic execution engines.To evaluate the effectiveness of our approach,we implemented a prototype obfuscation tool and tested it against prominent symbolic execution engines.Experimental results demonstrate that our approach signifi-cantly increases resilience against symbolic execution attacks while maintaining acceptable performance overhead.This paper provides a robust and scalable obfuscation technique,contributing to the enhancement of software protection strategies in adversarial environments.展开更多
Networking,storage,and hardware are just a few of the virtual computing resources that the infrastruc-ture service model offers,depending on what the client needs.One essential aspect of cloud computing that improves ...Networking,storage,and hardware are just a few of the virtual computing resources that the infrastruc-ture service model offers,depending on what the client needs.One essential aspect of cloud computing that improves resource allocation techniques is host load prediction.This difficulty means that hardware resource allocation in cloud computing still results in hosting initialization issues,which add several minutes to response times.To solve this issue and accurately predict cloud capacity,cloud data centers use prediction algorithms.This permits dynamic cloud scalability while maintaining superior service quality.For host prediction,we therefore present a hybrid convolutional neural network long with short-term memory model in this work.First,the suggested hybrid model is input is subjected to the vector auto regression technique.The data in many variables that,prior to analysis,has been filtered to eliminate linear interdependencies.After that,the persisting data are processed and sent into the convolutional neural network layer,which gathers intricate details about the utilization of each virtual machine and central processing unit.The next step involves the use of extended short-term memory,which is suitable for representing the temporal information of irregular trends in time series components.The key to the entire process is that we used the most appropriate activation function for this type of model a scaled polynomial constant unit.Cloud systems require accurate prediction due to the increasing degrees of unpredictability in data centers.Because of this,two actual load traces were used in this study’s assessment of the performance.An example of the load trace is in the typical dispersed system.In comparison to CNN,VAR-GRU,VAR-MLP,ARIMA-LSTM,and other models,the experiment results demonstrate that our suggested approach offers state-of-the-art performance with higher accuracy in both datasets.展开更多
In order to solve the black-box modeling problem and improve the prediction accuracy of model,two distinguished models for tensile strength(Ts)and yield strength(Ys)of hot-rolled strip steel are established based on t...In order to solve the black-box modeling problem and improve the prediction accuracy of model,two distinguished models for tensile strength(Ts)and yield strength(Ys)of hot-rolled strip steel are established based on the industrial hot-rolled data and the algorithm of gene expression programming(GEP).Firstly,the industrial data of hot-rolled strip steel are preprocessed using the Pauta criterion,so as to eliminate outliers.The key input variables that affect Ys and Ts are selected by using the method of the maximal information coefficient(MIC).Secondly,the explicit prediction models of Ys and Ts are established using GEP.Subsequently,the model results based on GEP are compared with those based on the support vector regression(SVR)and the back propagation neural network(BPNN).Finally,the mathematical expression models for Ys and Ts obtained by GEP are used to further analyse the specific relationships between the chemical composition and mechanical property.It is shown that the errors of Ys and Ts based on GEP are less than 4%,and the coefficient of determination(R2)of Ys and Ts based on GEP is above 0.9,which has strong prediction performance.The prediction accuracy of GEP can achieve the same level with SVR and BPNN.It is worth mentioning that the proposed model can not only show the explicit relationship between the chemical composition,production process,and mechanical property of strip steel,but also occupy high prediction accuracy,which can make reliable reference for strip steel product design and optimisation.展开更多
Gastrointestinal stromal tumors(GISTs),the most prevalent mesenchymal tumors,often have poor outcomes due to high recurrence rates.However,the specific risk factors for GISTs,particularly those concerning the innate i...Gastrointestinal stromal tumors(GISTs),the most prevalent mesenchymal tumors,often have poor outcomes due to high recurrence rates.However,the specific risk factors for GISTs,particularly those concerning the innate immune-inflammatory response,remain poorly understood.This editorial highlights key prognostic factors that impact GIST progression and prognosis,while discussing the findings of a recent study that investigated the prognostic value of systemic inflammatory markers:systemic immune-inflammation index,neutrophil/lym-phocyte ratio,platelet/lymphocyte ratio,and monocyte/lymphocyte ratio,on recurrence-free survival in GIST patients.This editorial examines strategies to enhance the clinical applicability of the nomogram developed in the study,ensuring its effectiveness for robust implementation.Future directions outlined in the editorial stress the importance of integrating molecular insights,including KIT and PDGFRA mutations,tumor staging,and mitotic rates to refine predictive models.The editorial also underscores the value of multi-center studies to enhance the generalizability and clinical relevance of these approaches.By bridging inflammatory biomarkers with genetic and clinicopathologic factors,a more comprehensive understanding of GIST pathophysiology can be developed,paving the way for improved management strategies and patient outcomes.This perspective serves as a call to action for continued research into the interplay between genetic mutations,inflammatory marker modulation,and GIST progression,aiming to expand the scope of personalized oncology through a deeper understanding of GIST progression.展开更多
This study constructs a function-private inner-product predicate encryption(FP-IPPE)and achieves standard enhanced function privacy.The enhanced function privacy guarantees that a predicate secret key skf reveals noth...This study constructs a function-private inner-product predicate encryption(FP-IPPE)and achieves standard enhanced function privacy.The enhanced function privacy guarantees that a predicate secret key skf reveals nothing about the predicate f,as long as f is drawn from an evasive distribution with sufficient entropy.The proposed scheme extends the group-based public-key function-private predicate encryption(FP-PE)for“small superset predicates”proposed by Bartusek et al.(Asiacrypt 19),to the setting of inner-product predicates.This is the first construction of public-key FP-PE with enhanced function privacy security beyond the equality predicates,which is previously proposed by Boneh et al.(CRYPTO 13).The proposed construction relies on bilinear groups,and the security is proved in the generic bilinear group model.展开更多
This paper serves to help learners of English grammar precisely identify the function of the past participle form as an adjective or as a passive verb.Many learners get confused when trying to identify the function of...This paper serves to help learners of English grammar precisely identify the function of the past participle form as an adjective or as a passive verb.Many learners get confused when trying to identify the function of a past participle after a form of verb“be”.To differentiate between the functions of the past participle,some grammarians depend mainly on the context provided,while others apply certain handy tips to comprehend the exact function of it.The study aims to fill a gap about the difference between the two uses of the past participle.The study is qualitative in nature drawing mostly upon books,articles,and websites for data.Through examining some various viewpoints,it becomes clear that a past participle after a copula functioning as an adjective can be intensified by some adverbs such as“very”,and can be used as an attributive adjective in another structure.On the other hand,a past participle as a passive verb has a corresponding active form,can be extended to show the agent using a“by-phrase”,and does not logically accept to be preceded by an intensifier.展开更多
The evolution of Industry 4.0 made it essential to adopt the Internet of Things(IoT)and Cloud Computing(CC)technologies to perform activities in the new age of manufacturing.These technologies enable collecting,storin...The evolution of Industry 4.0 made it essential to adopt the Internet of Things(IoT)and Cloud Computing(CC)technologies to perform activities in the new age of manufacturing.These technologies enable collecting,storing,and retrieving essential information from the manufacturing stage.Data collected at sites are shared with others where execution automatedly occurs.The obtained information must be validated at manufacturing to avoid undesirable data losses during the de-manufacturing process.However,information sharing from the assembly level at the manufacturing stage to disassembly at the product end-of-life state is a major concern.The current research validates the information optimally to offer a minimum set of activities to complete the disassembly process.An optimal disassembly sequence plan(DSP)can possess valid information to organize the necessary actions in manufacturing.However,finding an optimal DSP is complex because of its combinatorial nature.The genetic algorithm(GA)is a widely preferred artificial intelligence(AI)algorithm to obtain a near-optimal solution for the DSP problem.The converging nature at local optima is a limitation in the traditional GA.This study improvised the GA workability by integrating with the proposed priori crossover operator.An optimality function is defined to reduce disassembly effort by considering directional changes as parameters.The enhanced GA method is tested on a real-time product to evaluate the performance.The obtained results reveal that diversity control depends on the operators employed in the disassembly attributes.The proposed method’s solution can be stored in the cloud and shared through IoT devices for effective resource allocation and disassembly for maximum recovery of the product.The effectiveness of the proposed enhanced GA method is determined by making a comparative assessment with traditional GA and other AI methods at different population sizes.展开更多
Due to the nature of ultra-short-acting opioid remifentanil of high time-varying,complex compartment model and low-accuracy of plasma concentration prediction,the traditional estimation method of population pharmacoki...Due to the nature of ultra-short-acting opioid remifentanil of high time-varying,complex compartment model and low-accuracy of plasma concentration prediction,the traditional estimation method of population pharmacokinetics parameters,nonlinear mixed effects model(NONMEM),has the abuses of tedious work and plenty of man-made jamming factors.The Elman feedback neural network was built.The relationships between the patients’plasma concentration of remifentanil and time,patient’age,gender,lean body mass,height,body surface area,sampling time,total dose,and injection rate through network training were obtained to predict the plasma concentration of remifentanil,and after that,it was compared with the results of NONMEM algorithm.In conclusion,the average error of Elman network is 6.34%,while that of NONMEM is 18.99%.The absolute average error of Elman network is 27.07%,while that of NONMEM is 38.09%.The experimental results indicate that Elman neural network could predict the plasma concentration of remifentanil rapidly and stably,with high accuracy and low error.For the characteristics of simple principle and fast computing speed,this method is suitable to data analysis of short-acting anesthesia drug population pharmacokinetic and pharmacodynamics.展开更多
Based on the theory of the quasi-truth degrees in two-valued predicate logic, some researches on approximate reasoning are studied in this paper. The relation of the pseudo-metric between first-order formulae and the ...Based on the theory of the quasi-truth degrees in two-valued predicate logic, some researches on approximate reasoning are studied in this paper. The relation of the pseudo-metric between first-order formulae and the quasi-truth degrees of first-order formulae is discussed, and it is proved that there is no isolated point in the logic metric space (F, ρ ). Thus the pseudo-metric between first-order formulae is well defined to develop the study about approximate reasoning in the logic metric space (F, ρ ). Then, three different types of approximate reasoning patterns are proposed, and their equivalence under some condition is proved. This work aims at filling in the blanks of approximate reasoning in quantitative predicate logic.展开更多
The pozzolanic activity of coal gangue, which is calcining at 500 to 1 000 ℃, differs distinctly. The simplex-centroid design with upper and lower bounds of component proportion is adopted to study the compressive st...The pozzolanic activity of coal gangue, which is calcining at 500 to 1 000 ℃, differs distinctly. The simplex-centroid design with upper and lower bounds of component proportion is adopted to study the compressive strength of mortars made with ternary blends of cement, activated coal gangue and fly ash. Based on the results of a minimum of seven design points, three special cubic polynomial models are used to establish the strength predicating equations at different ages for mortars. Five experimental checkpoints were also designed to verify the precision of the equations. The most frequent errors of the predicted values are within 3%. A simple and practical way is provided for determining the optimal proportion of two admixtures when they are used in concrete.展开更多
It has been known that the productivity of artesian wells is strongly dependent on the rheological properties of crude oils. This work targets two deep artesian wells(>5000 m) that are producing heavy crude oil. Th...It has been known that the productivity of artesian wells is strongly dependent on the rheological properties of crude oils. This work targets two deep artesian wells(>5000 m) that are producing heavy crude oil. The impacts of well conditions including temperature, pressure and shear rate, on the crude oil rheology were comprehensively investigated and correlated using several empirical rheological models. The experimental data indicate that this heavy oil is very sensitive to temperature as result of microstructure change caused by hydrogen bonding. The rheological behavior of the heavy oil is also significantly impacted by the imposed pressure, i.e., the viscosity flow activation energy(Eμ) gently increases with the increasing pressure. The viscosity–shear rate data are well fitted to the power law model at low temperature. However, due to the transition of fluid feature at high temperature(Newtonian fluid), the measured viscosity was found to slightly deviate from the fitting data. Combining the evaluated correlations, the viscosity profile of the heavy crude oil in these two deep artesian wells as a function of well depth was predicted using the oilfield producing data.展开更多
In this paper, a formal approach based on predicate logic is proposed for representing and reasoning of trusted computing models. Predicates are defined to represent the characteristics of the objects and the relation...In this paper, a formal approach based on predicate logic is proposed for representing and reasoning of trusted computing models. Predicates are defined to represent the characteristics of the objects and the relationship among these objects in a trusted system according to trusted computing specifications. Inference rules of trusted relation are given too. With the semantics proposed, some trusted computing models are formalized and verified, which shows that Predicate calculus logic provides a general and effective method for modeling and reasoning trusted computing systems.展开更多
By analyzing the metallogenic conditions and prospecting marks of F 8 fault belt in Shiujingtun Gold Mine, the geochemical samples were collected along F 8 fault belt and prospecting profile normal to the F 8 fault be...By analyzing the metallogenic conditions and prospecting marks of F 8 fault belt in Shiujingtun Gold Mine, the geochemical samples were collected along F 8 fault belt and prospecting profile normal to the F 8 fault belt. Gold and its indicator elements were tested with X ray fluorescence spectrometry and the content distribution diagram of Au, Ag, Hg and As along the F 8 fault belt was performed. The geochemical primary halo model and the Grey system model of F 8 fault belt are established. With these element distribution features and models, the blind ore bodies in the F 8 fault belt were predicted. Engineering prospect shows that the industrial orebodies have been discovered and the prediction results are dependable.展开更多
SOZL (structured methodology + object-oriented methodology + Z language) is a language that attempts to integrate structured method, object-oriented method and formal method. The core of this language is predicate dat...SOZL (structured methodology + object-oriented methodology + Z language) is a language that attempts to integrate structured method, object-oriented method and formal method. The core of this language is predicate data flow diagram (PDFD). In order to eliminate the ambiguity of predicate data flow diagrams and their associated textual specifications, a formalization of the syntax and semantics of predicate data flow diagrams is necessary. In this paper we use Z notation to define an abstract syntax and the related structural constraints for the PDFD notation, and provide it with an axiomatic semantics based on the concept of data availability and functionality of predicate operation. Finally, an example is given to establish functionality consistent decomposition on hierarchical PDFD (HPDFD).展开更多
Automatic Question Answer System(QAS)is a kind of high-powered software system based on Internet.Its key technology is the interrelated technology based on natural language understanding,including the construction of ...Automatic Question Answer System(QAS)is a kind of high-powered software system based on Internet.Its key technology is the interrelated technology based on natural language understanding,including the construction of knowledge base and corpus,the Word Segmentation and POS Tagging of text,the Grammatical Analysis and Semantic Analysis of sentences etc.This thesis dissertated mainly the denotation of knowledge-information based on semantic network in QAS,the stochastic syntax-parse model named LSF of knowledge-information in QAS,the structure and constitution of QAS.And the LSF model's parameters were exercised,which proved that they were feasible.At the same time,through "the limited-domain QAS" which was exploited for banks by us,these technologies were proved effective and propagable.展开更多
The vapor-liquid equilibrium of Dimethyl Carbonate-Methanol-Furfural under atmospheric pressure from DMC-CH 3OH,DMCC 5H 4O 2,CH 3OH-C 5H 4O 2 binary systematic VLE data is calculated,by using C ++(VC6.0) programming l...The vapor-liquid equilibrium of Dimethyl Carbonate-Methanol-Furfural under atmospheric pressure from DMC-CH 3OH,DMCC 5H 4O 2,CH 3OH-C 5H 4O 2 binary systematic VLE data is calculated,by using C ++(VC6.0) programming language and Wilson equation.It provided important VLE data to set up mathematic models of extraction-rectifying separation of DMC and methanol by using furfural as extraction reagent.So the results can be used for chemical engineering calculation.展开更多
According to the characteristic of Beidou Double-star positing system(for short:Double-star position),the optimal predication model of Double-star position/SINS integrated system is put forward,which can make use of t...According to the characteristic of Beidou Double-star positing system(for short:Double-star position),the optimal predication model of Double-star position/SINS integrated system is put forward,which can make use of the delayed position in-formation from Double-star positioning system to predicate optimally for the integrated system,and then to correct SINS,and af-fords integrated results of some navigation parameters.In order to validate the consistency of the filter,the criteria for consistency of a filter is also studied,and the tested statistics are given,the experiment based on practical measured data shows that the filtering method is consistent with the integrated system.展开更多
Web-services are highly distributed programs, and concurrent software is notoriously error-prone. Model checking is a powerful technique to find bugs in concurrent systems. However, the existing model checkers have no...Web-services are highly distributed programs, and concurrent software is notoriously error-prone. Model checking is a powerful technique to find bugs in concurrent systems. However, the existing model checkers have no enough ability to support for the programming languages and communication mechanisms used for Web services. We propose to use Kripke structures as means of modeling Web service. This paper presents an automated way to extract formal models from programs implementing Web services using predicate abstraction for abstract model checking. The abstract models are checked by means of a model checker that implements automatic abstraction refinement. These results enable the verification of the applications that implement Web services.展开更多
基金Supported by the National Natural Science Foundation of China under Grant Nos.61331011 and 61273320the National High Technology Research and Development 863 Program of China under Grant No.2012AA011102the Natural Science Foundation of Jiangsu Provincial Department of Education under Grant No.10KJB520016
摘要This paper explores a tree kernel based method for semantic role labeling(SRL)of Chinese nominal predicates via a convolution tree kernel.In particular,a new parse tree representation structure,called dependency-driven constituent parse tree(D-CPT),is proposed to combine the advantages of both constituent and dependence parse trees.This is achieved by directly representing various kinds of dependency relations in a CPT-style structure,which employs dependency relation types instead of phrase labels in CPT(Constituent Parse Tree).In this way,D-CPT not only keeps the dependency relationship information in the dependency parse tree(DPT)structure but also retains the basic hierarchical structure of CPT style.Moreover,several schemes are designed to extract various kinds of necessary information,such as the shortest path between the nominal predicate and the argument candidate,the support verb of the nominal predicate and the head argument modified by the argument candidate,from D-CPT.This largely reduces the noisy information inherent in D-CPT.Finally,a convolution tree kernel is employed to compute the similarity between two parse trees.Besides,we also implement a feature-based method based on D-CPT.Evaluation on Chinese NomBank corpus shows that our tree kernel based method on D-CPT performs significantly better than other tree kernel-based ones and achieves comparable performance with the state-of-the-art feature-based ones.This indicates the effectiveness of the novel D-CPT structure in representing various kinds of dependency relations in a CPT-style structure and our tree kernel based method in exploring the novel D-CPT structure.This also illustrates that the kernel-based methods are competitive and they are complementary with the feature-based methods on SRL.
摘要Frege argued that a predicate was a functional expression and the reference of it a concept, which as a predicative function had one or more empty places and was thus incomplete. Frege's view gives rise to what has been known as the paradox of the concept "horse." In order to resolve this paradox, I argue for an opposite view which retains the point that a predicate is a function, i.e. that a predicative function is complete in a sense. Specifically speaking, a predicate performing the function of a predicate has at least one empty place and has no reference, while a predicate performing the function of a subject does not have any empty place but does have a reference. Frege not only regarded a concept with one or more empty places as the reference of a predicate but also took a set of objects without any empty place to be the extension of a concept with one or more empty places. Thus, it presents a complex relationship between the reference of a predicate and its corresponding extension, leading to disharmony in his theory. I argue that this is because there is a major defect in Frege's theory of meaning, namely the neglect of common names. What he called extensions of concepts are actually extensions of common names, and the references of predicates and the extensions of common names have a substantial difference despite being closely related.
基金supported byOpen Foundation of Key Laboratory of Cyberspace Security,Ministry of Education of China(No.KLCS20240211)Henan Science and Technology Major Project No.241110210100.
摘要Code obfuscation is a crucial technique for protecting software against reverse engineering and security attacks.Among various obfuscation methods,opaque predicates,which are recognized as flexible and promising,are widely used to increase control-flow complexity.However,traditional opaque predicates are increasingly vulnerable to Dynamic Symbolic Execution(DSE)attacks,which can efficiently identify and eliminate them.To address this issue,this paper proposes a novel approach for anti-DSE opaque predicates that effectively resists symbolic execution-based deobfuscation.Our method introduces two key techniques:single-way function opaque predicates,which leverage hash functions and logarithmic transformations to prevent constraint solvers from generating feasible inputs,and path-explosion opaque predicates,which generate an excessive number of execution paths,overwhelming symbolic execution engines.To evaluate the effectiveness of our approach,we implemented a prototype obfuscation tool and tested it against prominent symbolic execution engines.Experimental results demonstrate that our approach signifi-cantly increases resilience against symbolic execution attacks while maintaining acceptable performance overhead.This paper provides a robust and scalable obfuscation technique,contributing to the enhancement of software protection strategies in adversarial environments.
基金funded by Multimedia University(Ref:MMU/RMC/PostDoc/NEW/2024/9804).
摘要Networking,storage,and hardware are just a few of the virtual computing resources that the infrastruc-ture service model offers,depending on what the client needs.One essential aspect of cloud computing that improves resource allocation techniques is host load prediction.This difficulty means that hardware resource allocation in cloud computing still results in hosting initialization issues,which add several minutes to response times.To solve this issue and accurately predict cloud capacity,cloud data centers use prediction algorithms.This permits dynamic cloud scalability while maintaining superior service quality.For host prediction,we therefore present a hybrid convolutional neural network long with short-term memory model in this work.First,the suggested hybrid model is input is subjected to the vector auto regression technique.The data in many variables that,prior to analysis,has been filtered to eliminate linear interdependencies.After that,the persisting data are processed and sent into the convolutional neural network layer,which gathers intricate details about the utilization of each virtual machine and central processing unit.The next step involves the use of extended short-term memory,which is suitable for representing the temporal information of irregular trends in time series components.The key to the entire process is that we used the most appropriate activation function for this type of model a scaled polynomial constant unit.Cloud systems require accurate prediction due to the increasing degrees of unpredictability in data centers.Because of this,two actual load traces were used in this study’s assessment of the performance.An example of the load trace is in the typical dispersed system.In comparison to CNN,VAR-GRU,VAR-MLP,ARIMA-LSTM,and other models,the experiment results demonstrate that our suggested approach offers state-of-the-art performance with higher accuracy in both datasets.
基金supported by the National Natural Science Foundation of China(Grant Nos.52074187 and 52274388)Liaoning Province Artificial Intelligence Innovation and Development Plan Project(Major Science and Technology Project)(2023JH26-10100002)the National Key Research and Development Program of China(No.2022YFB3304800).
摘要In order to solve the black-box modeling problem and improve the prediction accuracy of model,two distinguished models for tensile strength(Ts)and yield strength(Ys)of hot-rolled strip steel are established based on the industrial hot-rolled data and the algorithm of gene expression programming(GEP).Firstly,the industrial data of hot-rolled strip steel are preprocessed using the Pauta criterion,so as to eliminate outliers.The key input variables that affect Ys and Ts are selected by using the method of the maximal information coefficient(MIC).Secondly,the explicit prediction models of Ys and Ts are established using GEP.Subsequently,the model results based on GEP are compared with those based on the support vector regression(SVR)and the back propagation neural network(BPNN).Finally,the mathematical expression models for Ys and Ts obtained by GEP are used to further analyse the specific relationships between the chemical composition and mechanical property.It is shown that the errors of Ys and Ts based on GEP are less than 4%,and the coefficient of determination(R2)of Ys and Ts based on GEP is above 0.9,which has strong prediction performance.The prediction accuracy of GEP can achieve the same level with SVR and BPNN.It is worth mentioning that the proposed model can not only show the explicit relationship between the chemical composition,production process,and mechanical property of strip steel,but also occupy high prediction accuracy,which can make reliable reference for strip steel product design and optimisation.
摘要Gastrointestinal stromal tumors(GISTs),the most prevalent mesenchymal tumors,often have poor outcomes due to high recurrence rates.However,the specific risk factors for GISTs,particularly those concerning the innate immune-inflammatory response,remain poorly understood.This editorial highlights key prognostic factors that impact GIST progression and prognosis,while discussing the findings of a recent study that investigated the prognostic value of systemic inflammatory markers:systemic immune-inflammation index,neutrophil/lym-phocyte ratio,platelet/lymphocyte ratio,and monocyte/lymphocyte ratio,on recurrence-free survival in GIST patients.This editorial examines strategies to enhance the clinical applicability of the nomogram developed in the study,ensuring its effectiveness for robust implementation.Future directions outlined in the editorial stress the importance of integrating molecular insights,including KIT and PDGFRA mutations,tumor staging,and mitotic rates to refine predictive models.The editorial also underscores the value of multi-center studies to enhance the generalizability and clinical relevance of these approaches.By bridging inflammatory biomarkers with genetic and clinicopathologic factors,a more comprehensive understanding of GIST pathophysiology can be developed,paving the way for improved management strategies and patient outcomes.This perspective serves as a call to action for continued research into the interplay between genetic mutations,inflammatory marker modulation,and GIST progression,aiming to expand the scope of personalized oncology through a deeper understanding of GIST progression.
基金National Key Research and Development Program of China(2021YFB3101402)National Natural Science Foundation of China(62202294)。
摘要This study constructs a function-private inner-product predicate encryption(FP-IPPE)and achieves standard enhanced function privacy.The enhanced function privacy guarantees that a predicate secret key skf reveals nothing about the predicate f,as long as f is drawn from an evasive distribution with sufficient entropy.The proposed scheme extends the group-based public-key function-private predicate encryption(FP-PE)for“small superset predicates”proposed by Bartusek et al.(Asiacrypt 19),to the setting of inner-product predicates.This is the first construction of public-key FP-PE with enhanced function privacy security beyond the equality predicates,which is previously proposed by Boneh et al.(CRYPTO 13).The proposed construction relies on bilinear groups,and the security is proved in the generic bilinear group model.
摘要This paper serves to help learners of English grammar precisely identify the function of the past participle form as an adjective or as a passive verb.Many learners get confused when trying to identify the function of a past participle after a form of verb“be”.To differentiate between the functions of the past participle,some grammarians depend mainly on the context provided,while others apply certain handy tips to comprehend the exact function of it.The study aims to fill a gap about the difference between the two uses of the past participle.The study is qualitative in nature drawing mostly upon books,articles,and websites for data.Through examining some various viewpoints,it becomes clear that a past participle after a copula functioning as an adjective can be intensified by some adverbs such as“very”,and can be used as an attributive adjective in another structure.On the other hand,a past participle as a passive verb has a corresponding active form,can be extended to show the agent using a“by-phrase”,and does not logically accept to be preceded by an intensifier.
基金The authors are grateful to the Raytheon Chair for Systems Engineering for funding.
摘要The evolution of Industry 4.0 made it essential to adopt the Internet of Things(IoT)and Cloud Computing(CC)technologies to perform activities in the new age of manufacturing.These technologies enable collecting,storing,and retrieving essential information from the manufacturing stage.Data collected at sites are shared with others where execution automatedly occurs.The obtained information must be validated at manufacturing to avoid undesirable data losses during the de-manufacturing process.However,information sharing from the assembly level at the manufacturing stage to disassembly at the product end-of-life state is a major concern.The current research validates the information optimally to offer a minimum set of activities to complete the disassembly process.An optimal disassembly sequence plan(DSP)can possess valid information to organize the necessary actions in manufacturing.However,finding an optimal DSP is complex because of its combinatorial nature.The genetic algorithm(GA)is a widely preferred artificial intelligence(AI)algorithm to obtain a near-optimal solution for the DSP problem.The converging nature at local optima is a limitation in the traditional GA.This study improvised the GA workability by integrating with the proposed priori crossover operator.An optimality function is defined to reduce disassembly effort by considering directional changes as parameters.The enhanced GA method is tested on a real-time product to evaluate the performance.The obtained results reveal that diversity control depends on the operators employed in the disassembly attributes.The proposed method’s solution can be stored in the cloud and shared through IoT devices for effective resource allocation and disassembly for maximum recovery of the product.The effectiveness of the proposed enhanced GA method is determined by making a comparative assessment with traditional GA and other AI methods at different population sizes.
基金Project(31200748)supported by the National Natural Science Foundation of China
摘要Due to the nature of ultra-short-acting opioid remifentanil of high time-varying,complex compartment model and low-accuracy of plasma concentration prediction,the traditional estimation method of population pharmacokinetics parameters,nonlinear mixed effects model(NONMEM),has the abuses of tedious work and plenty of man-made jamming factors.The Elman feedback neural network was built.The relationships between the patients’plasma concentration of remifentanil and time,patient’age,gender,lean body mass,height,body surface area,sampling time,total dose,and injection rate through network training were obtained to predict the plasma concentration of remifentanil,and after that,it was compared with the results of NONMEM algorithm.In conclusion,the average error of Elman network is 6.34%,while that of NONMEM is 18.99%.The absolute average error of Elman network is 27.07%,while that of NONMEM is 38.09%.The experimental results indicate that Elman neural network could predict the plasma concentration of remifentanil rapidly and stably,with high accuracy and low error.For the characteristics of simple principle and fast computing speed,this method is suitable to data analysis of short-acting anesthesia drug population pharmacokinetic and pharmacodynamics.
基金National Natural Science Foundation of China (No. 60875034)Spanish Ministry of Education and Science Fund,Spain (No.TIN-2009-0828)Spanish Regional Government (Junta de Andalucia) Fund,Spain (No. P08-TIC-3548)
摘要Based on the theory of the quasi-truth degrees in two-valued predicate logic, some researches on approximate reasoning are studied in this paper. The relation of the pseudo-metric between first-order formulae and the quasi-truth degrees of first-order formulae is discussed, and it is proved that there is no isolated point in the logic metric space (F, ρ ). Thus the pseudo-metric between first-order formulae is well defined to develop the study about approximate reasoning in the logic metric space (F, ρ ). Then, three different types of approximate reasoning patterns are proposed, and their equivalence under some condition is proved. This work aims at filling in the blanks of approximate reasoning in quantitative predicate logic.
基金The National Basic Research Program of China (973Program)(No2000CB610703)
摘要The pozzolanic activity of coal gangue, which is calcining at 500 to 1 000 ℃, differs distinctly. The simplex-centroid design with upper and lower bounds of component proportion is adopted to study the compressive strength of mortars made with ternary blends of cement, activated coal gangue and fly ash. Based on the results of a minimum of seven design points, three special cubic polynomial models are used to establish the strength predicating equations at different ages for mortars. Five experimental checkpoints were also designed to verify the precision of the equations. The most frequent errors of the predicted values are within 3%. A simple and practical way is provided for determining the optimal proportion of two admixtures when they are used in concrete.
基金Supported by the National Key Science&Technology Projects during 13th Five-Year Plan(2016ZX05053-003)Young Scholars Development fund of SWPU(201499010121)
摘要It has been known that the productivity of artesian wells is strongly dependent on the rheological properties of crude oils. This work targets two deep artesian wells(>5000 m) that are producing heavy crude oil. The impacts of well conditions including temperature, pressure and shear rate, on the crude oil rheology were comprehensively investigated and correlated using several empirical rheological models. The experimental data indicate that this heavy oil is very sensitive to temperature as result of microstructure change caused by hydrogen bonding. The rheological behavior of the heavy oil is also significantly impacted by the imposed pressure, i.e., the viscosity flow activation energy(Eμ) gently increases with the increasing pressure. The viscosity–shear rate data are well fitted to the power law model at low temperature. However, due to the transition of fluid feature at high temperature(Newtonian fluid), the measured viscosity was found to slightly deviate from the fitting data. Combining the evaluated correlations, the viscosity profile of the heavy crude oil in these two deep artesian wells as a function of well depth was predicted using the oilfield producing data.
基金Supported by the National High-Technology Re-search and Development Program ( 863 Program)China(2004AA113020)
摘要In this paper, a formal approach based on predicate logic is proposed for representing and reasoning of trusted computing models. Predicates are defined to represent the characteristics of the objects and the relationship among these objects in a trusted system according to trusted computing specifications. Inference rules of trusted relation are given too. With the semantics proposed, some trusted computing models are formalized and verified, which shows that Predicate calculus logic provides a general and effective method for modeling and reasoning trusted computing systems.
基金TheOutstandingYoungScientistsFoundation !(No496 2 5304)andtheKeyProgramofMinistryofScienceandTechnologyofChina !(No95 pre 3
摘要By analyzing the metallogenic conditions and prospecting marks of F 8 fault belt in Shiujingtun Gold Mine, the geochemical samples were collected along F 8 fault belt and prospecting profile normal to the F 8 fault belt. Gold and its indicator elements were tested with X ray fluorescence spectrometry and the content distribution diagram of Au, Ag, Hg and As along the F 8 fault belt was performed. The geochemical primary halo model and the Grey system model of F 8 fault belt are established. With these element distribution features and models, the blind ore bodies in the F 8 fault belt were predicted. Engineering prospect shows that the industrial orebodies have been discovered and the prediction results are dependable.
摘要SOZL (structured methodology + object-oriented methodology + Z language) is a language that attempts to integrate structured method, object-oriented method and formal method. The core of this language is predicate data flow diagram (PDFD). In order to eliminate the ambiguity of predicate data flow diagrams and their associated textual specifications, a formalization of the syntax and semantics of predicate data flow diagrams is necessary. In this paper we use Z notation to define an abstract syntax and the related structural constraints for the PDFD notation, and provide it with an axiomatic semantics based on the concept of data availability and functionality of predicate operation. Finally, an example is given to establish functionality consistent decomposition on hierarchical PDFD (HPDFD).
基金Sponsored by the National Natural Science Foundation of China(Grant No.60305009)the Ph.D Degree Teacher Foundation of North China Electric Power University(Grant No.H0585).
摘要Automatic Question Answer System(QAS)is a kind of high-powered software system based on Internet.Its key technology is the interrelated technology based on natural language understanding,including the construction of knowledge base and corpus,the Word Segmentation and POS Tagging of text,the Grammatical Analysis and Semantic Analysis of sentences etc.This thesis dissertated mainly the denotation of knowledge-information based on semantic network in QAS,the stochastic syntax-parse model named LSF of knowledge-information in QAS,the structure and constitution of QAS.And the LSF model's parameters were exercised,which proved that they were feasible.At the same time,through "the limited-domain QAS" which was exploited for banks by us,these technologies were proved effective and propagable.
摘要The vapor-liquid equilibrium of Dimethyl Carbonate-Methanol-Furfural under atmospheric pressure from DMC-CH 3OH,DMCC 5H 4O 2,CH 3OH-C 5H 4O 2 binary systematic VLE data is calculated,by using C ++(VC6.0) programming language and Wilson equation.It provided important VLE data to set up mathematic models of extraction-rectifying separation of DMC and methanol by using furfural as extraction reagent.So the results can be used for chemical engineering calculation.
摘要According to the characteristic of Beidou Double-star positing system(for short:Double-star position),the optimal predication model of Double-star position/SINS integrated system is put forward,which can make use of the delayed position in-formation from Double-star positioning system to predicate optimally for the integrated system,and then to correct SINS,and af-fords integrated results of some navigation parameters.In order to validate the consistency of the filter,the criteria for consistency of a filter is also studied,and the tested statistics are given,the experiment based on practical measured data shows that the filtering method is consistent with the integrated system.
基金the National Natural Science Foundation of China (60663005, 60563005)the Natural Science Foundation of Guangxi Province (0542036, 0728093, 0728089)
摘要Web-services are highly distributed programs, and concurrent software is notoriously error-prone. Model checking is a powerful technique to find bugs in concurrent systems. However, the existing model checkers have no enough ability to support for the programming languages and communication mechanisms used for Web services. We propose to use Kripke structures as means of modeling Web service. This paper presents an automated way to extract formal models from programs implementing Web services using predicate abstraction for abstract model checking. The abstract models are checked by means of a model checker that implements automatic abstraction refinement. These results enable the verification of the applications that implement Web services.