This paper focuses on fast algorithm for computing the assignment reduct in inconsistent incomplete decision systems. It is quite inconvenient to judge the assignment reduct directly ac-cording to its definition. We p...This paper focuses on fast algorithm for computing the assignment reduct in inconsistent incomplete decision systems. It is quite inconvenient to judge the assignment reduct directly ac-cording to its definition. We propose the judgment theorem for the assignment reduct in the inconsistent incomplete decision system, which greatly simplifies judging this type reduct. On such basis, we derive a novel attribute significance measure and construct the fast assignment reduction algorithm （F-ARA）, intended for com-puting the assignment reduct in inconsistent incomplete decision systems. Final y, we make a comparison between F-ARA and the discernibility matrix-based method by experiments on 13 Univer-sity of California at Irvine （UCI） datasets, and the experimental results prove that F-ARA is efficient and feasible.展开更多
This paper presents a new highly parallel algorithm for computing the minimum-norm least-squares solution of inconsistent linear equations Ax = b(A∈Rm×n,b∈R (A)). By this algorithm the solution x = A + b is obt...This paper presents a new highly parallel algorithm for computing the minimum-norm least-squares solution of inconsistent linear equations Ax = b(A∈Rm×n,b∈R (A)). By this algorithm the solution x = A + b is obtained in T = n(log2m + log2(n - r + 1) + 5) + log2m + 1 steps with P=mn processors when m × 2(n - 1) and with P = 2n(n - 1) processors otherwise.展开更多
In recent years,there has been a backlash of sorts and the authenticity of images has been routinely questioned.Seeing is no longer believing.There is an urgent need for robust image forensic techniques to expose phot...In recent years,there has been a backlash of sorts and the authenticity of images has been routinely questioned.Seeing is no longer believing.There is an urgent need for robust image forensic techniques to expose photo forgery.This paper proposed a novel and effective technique to expose image forgery using inconsistent reflection.More specifically,a new technique was presented to calculate reflection line midpoint,the definition of midpoint ratio was given,and three standards were proposed and employed to detect image forgery.Accuracy and effectiveness of the proposed technique were evaluated using a data set consisting of 200 authentic and forged images.Experimental results indicate that the proposed method can detect image forgery with very high success rate.展开更多
Traditionally, the AI community assumes that a knowledge base must be consistent. Despite that, there are many applications where, due to the existence of rules with exceptions, inconsistent knowledge must be consider...Traditionally, the AI community assumes that a knowledge base must be consistent. Despite that, there are many applications where, due to the existence of rules with exceptions, inconsistent knowledge must be considered. One way of restoring consistency is to withdraw conflicting rules;however, this will destroy part of the knowledge. Indeed, a better alternative would be to give precedence to exceptions. This paper proposes a dialogue system for coherent reasoning with inconsistent knowledge, which resolves conflicts by using precedence relations of three kinds: explicit precedence relation, which is synthesized from precedence rules;implicit precedence relation, which is synthesized from defeasible rules;mixed precedence relation, which is synthesized by combining explicit and implicit precedence relations.展开更多
HIV is a retrovirus that infects and impairs the cells and functions of the immune system. It has caused a great challenge to global public health systems and leads to Acquired Immunodeficiency Syndrome (AIDS), if not...HIV is a retrovirus that infects and impairs the cells and functions of the immune system. It has caused a great challenge to global public health systems and leads to Acquired Immunodeficiency Syndrome (AIDS), if not attended to in good time. Antiretroviral therapy is used for managing the virus in a patient’s lifetime. Some of the symptoms of the disease include lean body mass and many opportunistic infections. This study has developed a SIAT mathematical model to investigate the impact of inconsistency in treatment of the disease. The arising non-linear differential equations have been obtained and analyzed. The DFE and its stability have been obtained and the study found that it is locally asymptotically stable when the basic reproduction number is less than unity. The endemic equilibrium has been obtained and found to be globally asymptotically stable when the basic reproduction number is greater than unity. Numerical solutions have been obtained and analyzed to give the trends in the spread dynamics. The inconsistency in treatment uptake has been analyzed through the numerical solutions. The study found that when the treatment rate of those infected increases, it leads to an increase in treatment population, which slows down the spread of HIV and vice versa. An increase in the rate of treatment of those with AIDS leads to a decrease in the AIDS population, the reverse happens when this rate decreases. The study recommends that the community involvement in advocating for consistent treatment of HIV to curb the spread of the disease.展开更多
This article describes some dynamic aspects on dynastic utility incorporating two-sided altruism with an OLG setting. The special case is analyzed where the weights of two-sided altruism are dynamically inconsistent. ...This article describes some dynamic aspects on dynastic utility incorporating two-sided altruism with an OLG setting. The special case is analyzed where the weights of two-sided altruism are dynamically inconsistent. The Bellman equation for two-sided altruism proves to be reduced to one-sided dynamic problem, but the effective discount factor is different only in the current generation. It is shown that a contraction mapping result of value function cannot be achieved in general, and that there can locally exist an infinite number of self-consistent policy functions of the class C＂ with distinct steady states （indeterminacy of self-consistent, differentiable policy functions）.展开更多
Reasoning with inconsistent ontologies involves using an inconsistency reasoner to get meaningful answers from inconsistent ontologies. This paper introduces an improved inconsistency reasoner, which selects consisten...Reasoning with inconsistent ontologies involves using an inconsistency reasoner to get meaningful answers from inconsistent ontologies. This paper introduces an improved inconsistency reasoner, which selects consistent subsets using minimal inconsistent sets and a resolution method, to improve the run-time performance of the reasoning processing. A minimal inconsistent set contains a minimal explanation for the inconsistency of a given ontology. Thus, it can replace the consistency checking operation, which is executed frequently in existing approaches. When selecting subsets of the inconsistent ontology, formulas which can be directly or indirectly resolved with the negation of the query formula are selected because only those formulas affect the consequences of the reasoner. Therefore, the complexity of the reasoning processing is significantly reduced. Tests show that the run-time performance of the inconsistency reasoner is significantly improved.展开更多
In this paper, we study the problem of rule extraction from data sets using the rough set method. For inconsistent rules due to improper selection of split-points during discretization, and/or to lack of information, ...In this paper, we study the problem of rule extraction from data sets using the rough set method. For inconsistent rules due to improper selection of split-points during discretization, and/or to lack of information, we propose two methods to remove their inconsistency based on irregular decision tables. By using these methods, inconsistent rules are eliminated as far as possible, without affecting the remaining consistent rules. Experimental test indicates that use of the new method leads to an improvement in the mean accuracy of the extracted rules.展开更多
Dear Editor,Harnessing the power of the immune system via immune checkpoint inhibition has revolutionized the treatment paradigm of many malignancies,including hepatocellular carcinoma(HCC).1 Despite encouraging effic...Dear Editor,Harnessing the power of the immune system via immune checkpoint inhibition has revolutionized the treatment paradigm of many malignancies,including hepatocellular carcinoma(HCC).1 Despite encouraging efficacy seen with the immune checkpoint blockade(ICB)agents in a subset of patients with HCC,however,there remain a large number of HCC patients experience ICB resistance and failed to derive durable benefit from these agents.展开更多
Multi-task learning is to improve the performance of the model by transferring and exploiting common knowledge among tasks.Existing MTL works mainly focus on the scenario where label sets among multiple tasks(MTs)are ...Multi-task learning is to improve the performance of the model by transferring and exploiting common knowledge among tasks.Existing MTL works mainly focus on the scenario where label sets among multiple tasks(MTs)are usually the same,thus they can be utilized for learning across the tasks.However,the real world has more general scenarios in which each task has only a small number of training samples and their label sets are just partially overlapped or even not.Learning such MTs is more challenging because of less correlation information available among these tasks.For this,we propose a framework to learn these tasks by jointly leveraging both abundant information from a learnt auxiliary big task with sufficiently many classes to cover those of all these tasks and the information shared among those partiallyoverlapped tasks.In our implementation of using the same neural network architecture of the learnt auxiliary task to learn individual tasks,the key idea is to utilize available label information to adaptively prune the hidden layer neurons of the auxiliary network to construct corresponding network for each task,while accompanying a joint learning across individual tasks.Extensive experimental results demonstrate that our proposed method is significantly competitive compared to state-of-the-art methods.展开更多
In this era of big data, data are often collected from multiple sources that have different reliabilities, and there is inevitable conflict with respect to the various information obtained when it relates to the the s...In this era of big data, data are often collected from multiple sources that have different reliabilities, and there is inevitable conflict with respect to the various information obtained when it relates to the the same object.One important task is to identify the most trustworthy value out of all the conflicting claims, and this is known as truth discovery. Existing truth discovery methods simultaneously identify the most trustworthy information and source reliability degrees and are based on the idea that more reliable sources often provide more trustworthy information,and vice versa. However, there are often semantic constrains defined upon relational database, which can be violated by a single data source. To remove violations, an important task is to repair data to satisfy the constrains,and this is known as data cleaning. The two problems above may coexist, but considering them together can provide some benefits, and to the authors knowledge, this has not yet been the focus of any research. In this paper, therefore, a schema-decomposing based method is proposed to simultaneously discover the truth and to clean the data, with the aim of improving accuracy. Experimental results using real world data sets of notebooks and mobile phones, as well as simulated data sets, demonstrate the effectiveness and efficiency of our proposed method.展开更多
This paper investigates a time-inconsistent stochastic linear-quadratic problem with regime switching that is characterized via a finite-state Markov chain.Open-loop equilibrium control is studied in this paper whose ...This paper investigates a time-inconsistent stochastic linear-quadratic problem with regime switching that is characterized via a finite-state Markov chain.Open-loop equilibrium control is studied in this paper whose existence is characterized via Markov-chain-modulated forward-backward stochastic difference equations and generalized Riccati-like equations with jumps.展开更多
Purpose–Data integration is to combine data residing at different sources and to provide the users with a unified interface of these data.An important issue on data integration is the existence of conflicts among the...Purpose–Data integration is to combine data residing at different sources and to provide the users with a unified interface of these data.An important issue on data integration is the existence of conflicts among the different data sources.Data sources may conflict with each other at data level,which is defined as data inconsistency.The purpose of this paper is to aim at this problem and propose a solution for data inconsistency in data integration.Design/methodology/approach–A relational data model extended with data source quality criteria is first defined.Then based on the proposed data model,a data inconsistency solution strategy is provided.To accomplish the strategy,fuzzy multi-attribute decision-making(MADM)approach based on data source quality criteria is applied to obtain the results.Finally,users feedbacks strategies are proposed to optimize the result of fuzzy MADM approach as the final data inconsistent solution.Findings–To evaluate the proposed method,the data obtained from the sensors are extracted.Some experiments are designed and performed to explain the effectiveness of the proposed strategy.The results substantiate that the solution has a better performance than the other methods on correctness,time cost and stability indicators.Practical implications–Since the inconsistent data collected from the sensors are pervasive,the proposed method can solve this problem and correct the wrong choice to some extent.Originality/value–In this paper,for the first time the authors study the effect of users feedbacks on integration results aiming at the inconsistent data.展开更多
The food industry is evolving toward intelligence and digitalization,but is faced with challenges such as inconsistent standards and poor system compatibility due to lack of unified technical guidance.GB/T 46511-2025,...The food industry is evolving toward intelligence and digitalization,but is faced with challenges such as inconsistent standards and poor system compatibility due to lack of unified technical guidance.GB/T 46511-2025,General technical requirements for food digital factory,the first general technical national standard for food digital factory,was released recently.It bridges the gap in the industry,serving as the technical support and implementation framework for the intelligent and digital transformation of enterprises in the food industry.展开更多
Wastewater-based epidemiology has emerged as a transformative surveillance tool for estimating substance consumption and monitoring disease prevalence,particularly during the COVID-19 pandemic.It enables the populatio...Wastewater-based epidemiology has emerged as a transformative surveillance tool for estimating substance consumption and monitoring disease prevalence,particularly during the COVID-19 pandemic.It enables the population-level monitoring of illicit drug use,pathogen prevalence,and environmental pollutant exposure.In this perspective,we summarize the key challenges specific to the Chinese context:(1)Sampling inconsistencies,necessitating standardized 24-hour composite protocols with high-frequency autosamplers(≤15 min/event)to improve the representativeness of samples.展开更多
AIM: To identify the clinical outcomes of hepato-cellular carcinoma (HCC) patients with inconsistent α-fetoprotein (AFP) levels which were initially high and then low at recurrence.METHODS: We retrospectively include...AIM: To identify the clinical outcomes of hepato-cellular carcinoma (HCC) patients with inconsistent α-fetoprotein (AFP) levels which were initially high and then low at recurrence.METHODS: We retrospectively included 178 patients who underwent liver resection with high preoperative AFP levels (≥ 200 ng/dL). Sixty-nine HCC patients had recurrence during follow-up and were grouped by their AFP levels at recurrence: group Ⅰ, AFP ≤ 20 ng/dL (n = 16); group Ⅱ, AFP 20-200 ng/dL (n = 24); and group Ⅲ, AFP ≥ 200 ng/dL (n = 29). Their preoperative clinical characteristics, accumulated recurrence rate, and recurrence-to-death survival rate were compared. Three patients, one in each group, underwentliver resection twice for primary and recurrent HCC. AFP immunohistochemistry of primary and recurrent HCC specimens were examined.RESULTS: In this study, 23% of patients demon-strated normal AFP levels at HCC recurrence. The AFP levels in these patients were initially high. There were no significant differences in clinical characteristics between the three groups except for the mean recur-rence interval (21.8 ± 14.6, 12.3 ± 7.7, 8.3 ± 6.6 mo, respectively, P < 0.001) and survival time (40.2 ± 19.9, 36.1 ± 22.4, 21.9 ± 22.0 mo, respectively, P = 0.013). Tumor size > 5 cm, total bilirubin > 1.2 mg/dL, vessel invasion, Child classification B, group Ⅲ, and recurrence interval < 12 mo, were risk factors for survival rate. Cox regression analysis was performed and vessel invasion, group Ⅲ, and recurrence interval were independent risk factors. The recurrence inter-val was significant longer in group Ⅰ (P < 0.001). The recurrence-to-death survival rate was significantly bet-ter in group Ⅱ (P = 0.016). AFP staining was strong in the primary HCC specimens and was reduced at recur-rence in group Ⅰ specimens.CONCLUSION: Patients in group Ⅰ with inconsistent AFP levels had a longer recurrence interval and worse recurrence-to-death survival rate than those in group Ⅱ. This clinical presentation may be caused by a delay in the detection of HCC recurrence.展开更多
Fault detection and diagnosis(FDD) facilitates reliable operation of systems. Various approaches have been proposed for FDD like Analytical redundancy(AR), Principal component analysis(PCA), Discrete event system(DES)...Fault detection and diagnosis(FDD) facilitates reliable operation of systems. Various approaches have been proposed for FDD like Analytical redundancy(AR), Principal component analysis(PCA), Discrete event system(DES) model etc., in the literature. Performance of FDD schemes greatly depends on accuracy of the sensors which measure the system parameters.Due to various reasons like faults, communication errors etc.,sensors may occasionally miss or report erroneous values of some system parameters to FDD engine, resulting in measurement inconsistency of these parameters. Schemes like AR, PCA etc.,have mechanisms to handle measurement inconsistency, however,they are computationally heavy. DES based FDD techniques are widely used because of computational simplicity, but they cannot handle measurement inconsistency efficiently. Existing DES based schemes do not use Measurement inconsistent(MI)parameters for FDD. These parameters are not permanently unmeasurable or erroneous, so ignoring them may lead to weak diagnosis. To address this issue, we propose a Measurement inconsistent discrete event system(MIDES) framework, which uses MI parameters for FDD at the instances they are measured by the sensors. Otherwise, when they are unmeasurable or erroneously reported, the MIDES invokes an estimator diagnoser that predicts the state(s) the system is expected to be in, using the subsequent parameters measured by the other sensors. The efficacy of the proposed method is illustrated using a pumpvalve system. In addition, an MIDES based intrusion detection system has been developed for detection of rogue dynamic host configuration protocol(DHCP) server attack by mapping the attack to a fault in the DES framework.展开更多
In order to evaluate the performance of a molecular Hain line probe assay （Hain LPA） for rapid detection of rifampicin and isoniazid resistance of Mycobocterium tuberculosis in China, 1612 smear positive patients we...In order to evaluate the performance of a molecular Hain line probe assay （Hain LPA） for rapid detection of rifampicin and isoniazid resistance of Mycobocterium tuberculosis in China, 1612 smear positive patients were consecutively enrolled in this study. Smear positive sputum specimens were collected for Hain LPA and conventional drug susceptibility testing （DST）. The sensitivity and specificity of Hain LPA were analyzed by using conventional DST as golden reference. The sensitivity, specificity, positive predictive value {PPV） and negative predictive value （NPV） for rifampicin resistance detection were 88.33%, 97.66%, 81.54%, and 98.62%, respectively. The sensitivity, specificity, PPV and NPV for isoniazid resistance detection were 80.25%, 98.07%, 87.25%, and 96.78%, respectively. These findings suggested that Hain LPA can be an effective method worthy of broader use in China.展开更多
基金supported by the National Natural Science Foundation of China(61363047)the Jiangxi Education Department(GJJ13760)the Science and Technology Support Foundation of Jiangxi Province(20111BBE50008)
文摘This paper focuses on fast algorithm for computing the assignment reduct in inconsistent incomplete decision systems. It is quite inconvenient to judge the assignment reduct directly ac-cording to its definition. We propose the judgment theorem for the assignment reduct in the inconsistent incomplete decision system, which greatly simplifies judging this type reduct. On such basis, we derive a novel attribute significance measure and construct the fast assignment reduction algorithm （F-ARA）, intended for com-puting the assignment reduct in inconsistent incomplete decision systems. Final y, we make a comparison between F-ARA and the discernibility matrix-based method by experiments on 13 Univer-sity of California at Irvine （UCI） datasets, and the experimental results prove that F-ARA is efficient and feasible.
基金This project is supported by the National Natural Science Foundation of China
文摘This paper presents a new highly parallel algorithm for computing the minimum-norm least-squares solution of inconsistent linear equations Ax = b(A∈Rm×n,b∈R (A)). By this algorithm the solution x = A + b is obtained in T = n(log2m + log2(n - r + 1) + 5) + log2m + 1 steps with P=mn processors when m × 2(n - 1) and with P = 2n(n - 1) processors otherwise.
基金Fundamental Research Funds for the Central Universities,China
文摘In recent years,there has been a backlash of sorts and the authenticity of images has been routinely questioned.Seeing is no longer believing.There is an urgent need for robust image forensic techniques to expose photo forgery.This paper proposed a novel and effective technique to expose image forgery using inconsistent reflection.More specifically,a new technique was presented to calculate reflection line midpoint,the definition of midpoint ratio was given,and three standards were proposed and employed to detect image forgery.Accuracy and effectiveness of the proposed technique were evaluated using a data set consisting of 200 authentic and forged images.Experimental results indicate that the proposed method can detect image forgery with very high success rate.
文摘Traditionally, the AI community assumes that a knowledge base must be consistent. Despite that, there are many applications where, due to the existence of rules with exceptions, inconsistent knowledge must be considered. One way of restoring consistency is to withdraw conflicting rules;however, this will destroy part of the knowledge. Indeed, a better alternative would be to give precedence to exceptions. This paper proposes a dialogue system for coherent reasoning with inconsistent knowledge, which resolves conflicts by using precedence relations of three kinds: explicit precedence relation, which is synthesized from precedence rules;implicit precedence relation, which is synthesized from defeasible rules;mixed precedence relation, which is synthesized by combining explicit and implicit precedence relations.
文摘HIV is a retrovirus that infects and impairs the cells and functions of the immune system. It has caused a great challenge to global public health systems and leads to Acquired Immunodeficiency Syndrome (AIDS), if not attended to in good time. Antiretroviral therapy is used for managing the virus in a patient’s lifetime. Some of the symptoms of the disease include lean body mass and many opportunistic infections. This study has developed a SIAT mathematical model to investigate the impact of inconsistency in treatment of the disease. The arising non-linear differential equations have been obtained and analyzed. The DFE and its stability have been obtained and the study found that it is locally asymptotically stable when the basic reproduction number is less than unity. The endemic equilibrium has been obtained and found to be globally asymptotically stable when the basic reproduction number is greater than unity. Numerical solutions have been obtained and analyzed to give the trends in the spread dynamics. The inconsistency in treatment uptake has been analyzed through the numerical solutions. The study found that when the treatment rate of those infected increases, it leads to an increase in treatment population, which slows down the spread of HIV and vice versa. An increase in the rate of treatment of those with AIDS leads to a decrease in the AIDS population, the reverse happens when this rate decreases. The study recommends that the community involvement in advocating for consistent treatment of HIV to curb the spread of the disease.
文摘This article describes some dynamic aspects on dynastic utility incorporating two-sided altruism with an OLG setting. The special case is analyzed where the weights of two-sided altruism are dynamically inconsistent. The Bellman equation for two-sided altruism proves to be reduced to one-sided dynamic problem, but the effective discount factor is different only in the current generation. It is shown that a contraction mapping result of value function cannot be achieved in general, and that there can locally exist an infinite number of self-consistent policy functions of the class C＂ with distinct steady states （indeterminacy of self-consistent, differentiable policy functions）.
基金Supported by the Specialized Research Fund for the Doctoral Program of Higher Education of MOE, P.R.C (No.20096102120037)
文摘Reasoning with inconsistent ontologies involves using an inconsistency reasoner to get meaningful answers from inconsistent ontologies. This paper introduces an improved inconsistency reasoner, which selects consistent subsets using minimal inconsistent sets and a resolution method, to improve the run-time performance of the reasoning processing. A minimal inconsistent set contains a minimal explanation for the inconsistency of a given ontology. Thus, it can replace the consistency checking operation, which is executed frequently in existing approaches. When selecting subsets of the inconsistent ontology, formulas which can be directly or indirectly resolved with the negation of the query formula are selected because only those formulas affect the consequences of the reasoner. Therefore, the complexity of the reasoning processing is significantly reduced. Tests show that the run-time performance of the inconsistency reasoner is significantly improved.
基金the Basic Research Foundation of Tsinghua University (No. JC2001029) and the National High-Tech Research and Development Program of China (No. 863-511-930-004)
文摘In this paper, we study the problem of rule extraction from data sets using the rough set method. For inconsistent rules due to improper selection of split-points during discretization, and/or to lack of information, we propose two methods to remove their inconsistency based on irregular decision tables. By using these methods, inconsistent rules are eliminated as far as possible, without affecting the remaining consistent rules. Experimental test indicates that use of the new method leads to an improvement in the mean accuracy of the extracted rules.
基金This work was supported by the National Natural Science Foundation of China(81920108025,81874229,82072633,and 82122047)the Innovative Research Team of High-level Local Universities in Shanghai(SHSMU-ZLCX20211602)Shanghai Natural Science Foundation(22ZR1480900).
文摘Dear Editor,Harnessing the power of the immune system via immune checkpoint inhibition has revolutionized the treatment paradigm of many malignancies,including hepatocellular carcinoma(HCC).1 Despite encouraging efficacy seen with the immune checkpoint blockade(ICB)agents in a subset of patients with HCC,however,there remain a large number of HCC patients experience ICB resistance and failed to derive durable benefit from these agents.
基金supported by the NSFC(Grant No.61672281)the Key Program of NSFC(No.61732006).
文摘Multi-task learning is to improve the performance of the model by transferring and exploiting common knowledge among tasks.Existing MTL works mainly focus on the scenario where label sets among multiple tasks(MTs)are usually the same,thus they can be utilized for learning across the tasks.However,the real world has more general scenarios in which each task has only a small number of training samples and their label sets are just partially overlapped or even not.Learning such MTs is more challenging because of less correlation information available among these tasks.For this,we propose a framework to learn these tasks by jointly leveraging both abundant information from a learnt auxiliary big task with sufficiently many classes to cover those of all these tasks and the information shared among those partiallyoverlapped tasks.In our implementation of using the same neural network architecture of the learnt auxiliary task to learn individual tasks,the key idea is to utilize available label information to adaptively prune the hidden layer neurons of the auxiliary network to construct corresponding network for each task,while accompanying a joint learning across individual tasks.Extensive experimental results demonstrate that our proposed method is significantly competitive compared to state-of-the-art methods.
基金partially supported by the Key Research and Development Plan of National Ministry of Science and Technology (No. 2016YFB1000703)the Key Program of the National Natural Science Foundation of China (Nos. 61190115, 61472099, 61632010, and U1509216)+2 种基金National Sci-Tech Support Plan (No. 2015BAH10F01)the Scientific Research Foundation for the Returned Overseas Chinese Scholars of Heilongjiang Province (No. LC2016026)MOE-Microsoft Key Laboratory of Natural Language Processing and Speech, Harbin Institute of Technology
文摘In this era of big data, data are often collected from multiple sources that have different reliabilities, and there is inevitable conflict with respect to the various information obtained when it relates to the the same object.One important task is to identify the most trustworthy value out of all the conflicting claims, and this is known as truth discovery. Existing truth discovery methods simultaneously identify the most trustworthy information and source reliability degrees and are based on the idea that more reliable sources often provide more trustworthy information,and vice versa. However, there are often semantic constrains defined upon relational database, which can be violated by a single data source. To remove violations, an important task is to repair data to satisfy the constrains,and this is known as data cleaning. The two problems above may coexist, but considering them together can provide some benefits, and to the authors knowledge, this has not yet been the focus of any research. In this paper, therefore, a schema-decomposing based method is proposed to simultaneously discover the truth and to clean the data, with the aim of improving accuracy. Experimental results using real world data sets of notebooks and mobile phones, as well as simulated data sets, demonstrate the effectiveness and efficiency of our proposed method.
基金the National Key R&D Program of China under Grant No.2018YFA0703800the National Natural Science Foundation of China under Grant Nos.61773222,61877057 and 61973172。
文摘This paper investigates a time-inconsistent stochastic linear-quadratic problem with regime switching that is characterized via a finite-state Markov chain.Open-loop equilibrium control is studied in this paper whose existence is characterized via Markov-chain-modulated forward-backward stochastic difference equations and generalized Riccati-like equations with jumps.
文摘Purpose–Data integration is to combine data residing at different sources and to provide the users with a unified interface of these data.An important issue on data integration is the existence of conflicts among the different data sources.Data sources may conflict with each other at data level,which is defined as data inconsistency.The purpose of this paper is to aim at this problem and propose a solution for data inconsistency in data integration.Design/methodology/approach–A relational data model extended with data source quality criteria is first defined.Then based on the proposed data model,a data inconsistency solution strategy is provided.To accomplish the strategy,fuzzy multi-attribute decision-making(MADM)approach based on data source quality criteria is applied to obtain the results.Finally,users feedbacks strategies are proposed to optimize the result of fuzzy MADM approach as the final data inconsistent solution.Findings–To evaluate the proposed method,the data obtained from the sensors are extracted.Some experiments are designed and performed to explain the effectiveness of the proposed strategy.The results substantiate that the solution has a better performance than the other methods on correctness,time cost and stability indicators.Practical implications–Since the inconsistent data collected from the sensors are pervasive,the proposed method can solve this problem and correct the wrong choice to some extent.Originality/value–In this paper,for the first time the authors study the effect of users feedbacks on integration results aiming at the inconsistent data.
文摘The food industry is evolving toward intelligence and digitalization,but is faced with challenges such as inconsistent standards and poor system compatibility due to lack of unified technical guidance.GB/T 46511-2025,General technical requirements for food digital factory,the first general technical national standard for food digital factory,was released recently.It bridges the gap in the industry,serving as the technical support and implementation framework for the intelligent and digital transformation of enterprises in the food industry.
基金supported by the National Natural Science Foundation of China(Grant no.42307534)Discovery Project(DP220101790)+1 种基金The University of Queensland ScholarshipAustralian Research Council Discovery Project(DP220101790).
文摘Wastewater-based epidemiology has emerged as a transformative surveillance tool for estimating substance consumption and monitoring disease prevalence,particularly during the COVID-19 pandemic.It enables the population-level monitoring of illicit drug use,pathogen prevalence,and environmental pollutant exposure.In this perspective,we summarize the key challenges specific to the Chinese context:(1)Sampling inconsistencies,necessitating standardized 24-hour composite protocols with high-frequency autosamplers(≤15 min/event)to improve the representativeness of samples.
文摘AIM: To identify the clinical outcomes of hepato-cellular carcinoma (HCC) patients with inconsistent α-fetoprotein (AFP) levels which were initially high and then low at recurrence.METHODS: We retrospectively included 178 patients who underwent liver resection with high preoperative AFP levels (≥ 200 ng/dL). Sixty-nine HCC patients had recurrence during follow-up and were grouped by their AFP levels at recurrence: group Ⅰ, AFP ≤ 20 ng/dL (n = 16); group Ⅱ, AFP 20-200 ng/dL (n = 24); and group Ⅲ, AFP ≥ 200 ng/dL (n = 29). Their preoperative clinical characteristics, accumulated recurrence rate, and recurrence-to-death survival rate were compared. Three patients, one in each group, underwentliver resection twice for primary and recurrent HCC. AFP immunohistochemistry of primary and recurrent HCC specimens were examined.RESULTS: In this study, 23% of patients demon-strated normal AFP levels at HCC recurrence. The AFP levels in these patients were initially high. There were no significant differences in clinical characteristics between the three groups except for the mean recur-rence interval (21.8 ± 14.6, 12.3 ± 7.7, 8.3 ± 6.6 mo, respectively, P < 0.001) and survival time (40.2 ± 19.9, 36.1 ± 22.4, 21.9 ± 22.0 mo, respectively, P = 0.013). Tumor size > 5 cm, total bilirubin > 1.2 mg/dL, vessel invasion, Child classification B, group Ⅲ, and recurrence interval < 12 mo, were risk factors for survival rate. Cox regression analysis was performed and vessel invasion, group Ⅲ, and recurrence interval were independent risk factors. The recurrence inter-val was significant longer in group Ⅰ (P < 0.001). The recurrence-to-death survival rate was significantly bet-ter in group Ⅱ (P = 0.016). AFP staining was strong in the primary HCC specimens and was reduced at recur-rence in group Ⅰ specimens.CONCLUSION: Patients in group Ⅰ with inconsistent AFP levels had a longer recurrence interval and worse recurrence-to-death survival rate than those in group Ⅱ. This clinical presentation may be caused by a delay in the detection of HCC recurrence.
基金supported by TATA Consultancy Services(TCS),India through TCS Research Fellowship Program
文摘Fault detection and diagnosis(FDD) facilitates reliable operation of systems. Various approaches have been proposed for FDD like Analytical redundancy(AR), Principal component analysis(PCA), Discrete event system(DES) model etc., in the literature. Performance of FDD schemes greatly depends on accuracy of the sensors which measure the system parameters.Due to various reasons like faults, communication errors etc.,sensors may occasionally miss or report erroneous values of some system parameters to FDD engine, resulting in measurement inconsistency of these parameters. Schemes like AR, PCA etc.,have mechanisms to handle measurement inconsistency, however,they are computationally heavy. DES based FDD techniques are widely used because of computational simplicity, but they cannot handle measurement inconsistency efficiently. Existing DES based schemes do not use Measurement inconsistent(MI)parameters for FDD. These parameters are not permanently unmeasurable or erroneous, so ignoring them may lead to weak diagnosis. To address this issue, we propose a Measurement inconsistent discrete event system(MIDES) framework, which uses MI parameters for FDD at the instances they are measured by the sensors. Otherwise, when they are unmeasurable or erroneously reported, the MIDES invokes an estimator diagnoser that predicts the state(s) the system is expected to be in, using the subsequent parameters measured by the other sensors. The efficacy of the proposed method is illustrated using a pumpvalve system. In addition, an MIDES based intrusion detection system has been developed for detection of rogue dynamic host configuration protocol(DHCP) server attack by mapping the attack to a fault in the DES framework.
基金supported by Bill&Melinda Gates Foundation Tuberculosis Prevention and Control Project(2009-04-01)
文摘In order to evaluate the performance of a molecular Hain line probe assay （Hain LPA） for rapid detection of rifampicin and isoniazid resistance of Mycobocterium tuberculosis in China, 1612 smear positive patients were consecutively enrolled in this study. Smear positive sputum specimens were collected for Hain LPA and conventional drug susceptibility testing （DST）. The sensitivity and specificity of Hain LPA were analyzed by using conventional DST as golden reference. The sensitivity, specificity, positive predictive value {PPV） and negative predictive value （NPV） for rifampicin resistance detection were 88.33%, 97.66%, 81.54%, and 98.62%, respectively. The sensitivity, specificity, PPV and NPV for isoniazid resistance detection were 80.25%, 98.07%, 87.25%, and 96.78%, respectively. These findings suggested that Hain LPA can be an effective method worthy of broader use in China.
