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
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
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
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
In the current biomedical data movement, numerous efforts have been made to convert and normalize a large number of traditional structured and unstructured data (e.g., EHRs, reports) to semi-structured data (e.g., RDF...In the current biomedical data movement, numerous efforts have been made to convert and normalize a large number of traditional structured and unstructured data (e.g., EHRs, reports) to semi-structured data (e.g., RDF, OWL). With the increasing number of semi-structured data coming into the biomedical community, data integration and knowledge discovery from heterogeneous domains become important research problem. In the application level, detection of related concepts among medical ontologies is an important goal of life science research. It is more crucial to figure out how different concepts are related within a single ontology or across multiple ontologies by analysing predicates in different knowledge bases. However, the world today is one of information explosion, and it is extremely difficult for biomedical researchers to find existing or potential predicates to perform linking among cross domain concepts without any support from schema pattern analysis. Therefore, there is a need for a mechanism to do predicate oriented pattern analysis to partition heterogeneous ontologies into closer small topics and do query generation to discover cross domain knowledge from each topic. In this paper, we present such a model that predicates oriented pattern analysis based on their close relationship and generates a similarity matrix. Based on this similarity matrix, we apply an innovated unsupervised learning algorithm to partition large data sets into smaller and closer topics and generate meaningful queries to fully discover knowledge over a set of interlinked data sources. We have implemented a prototype system named BmQGen and evaluate the proposed model with colorectal surgical cohort from the Mayo Clinic.展开更多
Respectively belonging to different language families,English and Chinese naturally have many differences in morphology and syntax.This paper intends to give a contrastive analysis of subject and predicate in English ...Respectively belonging to different language families,English and Chinese naturally have many differences in morphology and syntax.This paper intends to give a contrastive analysis of subject and predicate in English and Chinese,focusing on differences of subject and predicate usages in the two languages,and the problems they cause for Chinese students in English learning and translation.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
A method to model and analyze the hybrid systems is presented. The time to be considered in the plant is taken as an explicit parameter through the constrained predicated net (CPN). The CPN's basic structure is a ...A method to model and analyze the hybrid systems is presented. The time to be considered in the plant is taken as an explicit parameter through the constrained predicated net (CPN). The CPN's basic structure is a Petri net with predicated transition. All components of the net are expressed by annotation which is defined on rational set Q. The analysis method for the plant is interval temporal logic represented by Petri nets. This paper combines the above two methods to synthesize the hybrid system, gives a simple and clear expression of the expected action of the studied plant.展开更多
This paper described an approach to make inferences on Chinese information using first order predicate logic, which could be used in the semantic query of Chinese. The predicates of the method were derived from the na...This paper described an approach to make inferences on Chinese information using first order predicate logic, which could be used in the semantic query of Chinese. The predicates of the method were derived from the natural language using rule based LFT, the axiom set was generated by extracting lexicon knowledge from HowNet, and the first order predicate inferences were made through symbol connection of center words. After all these were done, the evaluation and possible improvements of the method were provided. The experiment result shows a higher precision rate than that traditional methods can reach.展开更多
Cognitive grammar,as a linguistic theory that attaches importance to the relationship between language and thinking,provides us with a more comprehensive way to understand the structure,semantics and cognitive process...Cognitive grammar,as a linguistic theory that attaches importance to the relationship between language and thinking,provides us with a more comprehensive way to understand the structure,semantics and cognitive processing of noun predicate sentences.Therefore,under the framework of cognitive grammar,this paper tries to analyze the semantic connection and cognitive process in noun predicate sentences from the semantic perspective and the method of example theory,and discusses the motivation of the formation of this construction,so as to provide references for in-depth analysis of the cognitive laws behind noun predicate sentences.展开更多
基金National Key Research and Development Program of China(2021YFB3101402)National Natural Science Foundation of China(62202294)。
文摘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.
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.
文摘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).
文摘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.
文摘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 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)
文摘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.
文摘In the current biomedical data movement, numerous efforts have been made to convert and normalize a large number of traditional structured and unstructured data (e.g., EHRs, reports) to semi-structured data (e.g., RDF, OWL). With the increasing number of semi-structured data coming into the biomedical community, data integration and knowledge discovery from heterogeneous domains become important research problem. In the application level, detection of related concepts among medical ontologies is an important goal of life science research. It is more crucial to figure out how different concepts are related within a single ontology or across multiple ontologies by analysing predicates in different knowledge bases. However, the world today is one of information explosion, and it is extremely difficult for biomedical researchers to find existing or potential predicates to perform linking among cross domain concepts without any support from schema pattern analysis. Therefore, there is a need for a mechanism to do predicate oriented pattern analysis to partition heterogeneous ontologies into closer small topics and do query generation to discover cross domain knowledge from each topic. In this paper, we present such a model that predicates oriented pattern analysis based on their close relationship and generates a similarity matrix. Based on this similarity matrix, we apply an innovated unsupervised learning algorithm to partition large data sets into smaller and closer topics and generate meaningful queries to fully discover knowledge over a set of interlinked data sources. We have implemented a prototype system named BmQGen and evaluate the proposed model with colorectal surgical cohort from the Mayo Clinic.
文摘Respectively belonging to different language families,English and Chinese naturally have many differences in morphology and syntax.This paper intends to give a contrastive analysis of subject and predicate in English and Chinese,focusing on differences of subject and predicate usages in the two languages,and the problems they cause for Chinese students in English learning and translation.
文摘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).
文摘A method to model and analyze the hybrid systems is presented. The time to be considered in the plant is taken as an explicit parameter through the constrained predicated net (CPN). The CPN's basic structure is a Petri net with predicated transition. All components of the net are expressed by annotation which is defined on rational set Q. The analysis method for the plant is interval temporal logic represented by Petri nets. This paper combines the above two methods to synthesize the hybrid system, gives a simple and clear expression of the expected action of the studied plant.
文摘This paper described an approach to make inferences on Chinese information using first order predicate logic, which could be used in the semantic query of Chinese. The predicates of the method were derived from the natural language using rule based LFT, the axiom set was generated by extracting lexicon knowledge from HowNet, and the first order predicate inferences were made through symbol connection of center words. After all these were done, the evaluation and possible improvements of the method were provided. The experiment result shows a higher precision rate than that traditional methods can reach.
文摘Cognitive grammar,as a linguistic theory that attaches importance to the relationship between language and thinking,provides us with a more comprehensive way to understand the structure,semantics and cognitive processing of noun predicate sentences.Therefore,under the framework of cognitive grammar,this paper tries to analyze the semantic connection and cognitive process in noun predicate sentences from the semantic perspective and the method of example theory,and discusses the motivation of the formation of this construction,so as to provide references for in-depth analysis of the cognitive laws behind noun predicate sentences.
