Agricultural Investment Project Decisions Based on an Interactive Preference Disaggregation Model Considering Inconsistency

Agricultural investment project selection is a complex multi-criteria decision-making problem,as agricultural projects are easily influenced by various risk factors,and the evaluation information provided by decisionmakers usually involves uncertainty and inconsistency.Existing literature primarily employed direct preference elicitation methods to address such issues,necessitating a great cognitive effort on the part of decision-makers during evaluation,specifically,determining the weights of criteria.In this study,we propose an indirect preference elicitation method,known as a preference disaggregation method,to learn decision-maker preference models fromdecision examples.To enhance evaluation ease,decision-makers merely need to compare pairs of alternatives with which they are familiar,also known as reference alternatives.Probabilistic linguistic preference relations are employed to account for the presence of incomplete and uncertain information in such pairwise comparisons.To address the inconsistency among a group of decision-makers,we develop a pair of 0-1mixed integer programming models that consider both the semantics of linguistic terms and the belief degrees of decision-makers.Finally,we conduct a case study and comparative analysis.Results reveal the effectiveness of the proposed model in solving agricultural investment project selection problems with uncertain and inconsistent decision information.

Mathematical Modeling of the Co-Infection Dynamics of HIV and Tuberculosis Incorporating Inconsistency in HIV Treatment

A non-linear HIV-TB co-infection has been formulated and analyzed. The positivity and invariant region has been established. The disease free equilibrium and its stability has been determined. The local stability was determined and found to be stable under given conditions. The basic reproduction number was obtained and according to findings, co-infection diminishes when this number is less than unity, and persists when the number is greater than unity. The global stability of the endemic equilibrium was calculated. The impact of HIV on TB was established as well as the impact of TB on HIV. Numerical solution was also done and the findings indicate that when the rate of HIV treatment increases the latent TB increases while the co-infected population decreases. When the rate of HIV treatment decreases the latent TB population decreases and the co-infected population increases. Encouraging communities to prioritize the consistent treatment of HIV infected individuals must be emphasized in order to reduce the scourge of HIV-TB co-infection.

About the Strange Tree Paradox and Possible Inconsistency of Set Theory

The existence of “strange trees” is proven and their paradoxical nature is discussed, due to which set theory is suspected of being contradictory. All proofs rely on informal set-theoretic reasoning, but without using elements that were prohibited in axiomatic set theories in order to overcome the difficulties encountered by Cantor’s naive set theory. Therefore, in fact, the article deals with the possible inconsistency of existing axiomatic set theories, in particular, the ZFC theory. Strange trees appear when uncountable cardinals appear.

Resolving Electron Mass Inconsistency Using Negative Mass

In a previous publication, the author discussed the electron mass and charge inconsistencies resulting from classical models. A model was proposed using classical equations and two opposite charges to resolve the charge inconsistency. The model proposed in that article is modified herein using classical equations to define a model that also resolves the mass inconsistency. The positive mass of the outer shell of the electron core is replaced with a negative mass. The small negatively-charged core at the center still has positive mass.

Atomic Entailment and Atomic Inconsistency and Classical Entailment

In this paper we put forward a new solution of the well-known problem of relevant logics, i.e., we construct an atomic entailment. Hence, we construct a system of predicate calculus based on the atomic entailment. Next, we establish the definition of atomic inconsistency. The atomic inconsistency establishes an infinite class of inconsistent, but non-trivial systems. In this paper we construct the new definition of the classical entailment, into the bargain.

Effective Context Inconsistency Elimination Algorithm Based on Feedback and Reliability Distribution for loV

In recent years,context aware technology has been widely used in many fields,such as internet of vehicles(IoV).Consistent context information plays a vital role in adapting a system to rapidly changing situations.However,sensor's precision variance,equipment heterogeneity,network delay and the difference of statistical algorithms can lead to inconsistency context and inappropriate services.In this paper,we present an effective algorithm of context inconsistent elimination which is based on feedback and adjusted basic reliability distribution.Through feedback,each sensor's perception precision can be obtained,and with the adjusted basic reliability distribution scheme,we can make full use of all context information by adjusting the influence of every context on whole judgment based on sensor's perception precision and threshold of sensor's perception precision,and then eliminate context inconsistency.In order to evaluate the performance of the proposed context inconsistency elimination algorithm,context aware rate is defined.The simulation results show that the proposed context inconsistency elimination algorithm can obtain the best context aware rate in most cases for the varied error rates of sensors.

TIME INCONSISTENCY AND REPUTATION IN MONETARY POLICY: A STRATEGIC MODELLING IN CONTINUOUS TIME

This article develops a model to examine the equilibrium behavior of the time inconsistency problem in a continuous time economy with stochastic and endogenized distortion. First, the authors introduce the notion of sequentially rational equilibrium, and show that the time inconsistency problem may be solved with trigger reputation strategies for stochastic setting. The conditions for the existence of sequentially rational equilibrium are provided. Then, the concept of sequentially rational stochastically stable equilibrium is introduced. The authors compare the relative stability between the cooperative behavior and uncooperative behavior, and show that the cooperative equilibrium in this monetary policy game is a sequentially rational stochastically stable equilibrium and the uncooperative equilibrium is sequentially rational stochastically unstable equilibrium. In the long run, the zero inflation monetary policies are inherently more stable than the discretion rules, and once established, they tend to persist for longer periods of the time.

Pitfall of genome-wide association studies: Sources of inconsistency in genotypes and their effects

Personalized medicine will improve heath outcomes and patient satisfaction. However, implementing personalized medicine based on individuals’ biological information is far from simple, requiring genetic biomarkers that are mainly developed and used by the pharmaceutical companies for selecting those patients who benefit more, or have less risk of adverse drug reactions, from a particular drug. Genome-wide Association Studies (GWAS) aim to identify genetic variants across the human genome that might be utilized as genetic biomarkers for diagnosis and prognosis. During the last several years, high-density genotyping SNP arrays have facilitated GWAS that successfully identified common genetic variants associated with a variety of phenotypes. However, each of the identified genetic variants only explains a very small fraction of the underlying genetic contribution to the studied phenotypic trait. The replication studies demonstrated that only a small portion of associated loci in the initial GWAS can be replicated, even within the same populations. Given the complexity of GWAS, multiple sources of Type I (false positive) and Type II (false negative) errors exist. The inconsistency in genotypes that caused either by the genotypeing experiment or by genotype calling process is a major source of the false GWAS findings. Accurate and reproducible genotypes are paramount as inconsistency in genotypes can lead to an inflation of false associations. This article will review the sources of inconsistency in genotypes and discuss its effect in GWAS findings.

Inconsistency Quality Products （on Six Sigma Programs） Effect on Customer Loyality： Case Study of Industry ＂Tahu＂

Product ＂Tahu＂ is a traditional food of Sumedang city in Indonesia, and becomes an icon of the city. This study aims to see how consistent the quality of the products developed by small and medium-sized enterprises （SMEs） in the prosess six sigma program compliance effect on customer loyalty. The method used in this paper is descriptive exploratory. Based on a sample of 30 SMEs and 143 end-consumers, it showed that inconsistency in the quality common among SMEs with small production capacity size that gives discomfort to the consumer. Inconsistency in the quality values at each of SMEs which are distinguished by the production capacity is 3.301 or unclassified often inconsistent on a small scale SMEs, 3.460 or unclassified SMEs are often inconsistent in size and capacity being 4.227 or inconsistent unclassified rare or likely to be consistent on SMEs the size of the production capacity. Based on calculations using simple regression, suggest that the effect of dimensional consistency of product quality to customer loyalty is at 34%, while the balance of 66% is influenced by other variables such as promotion, competition level, location of the company etc.. It is recommended for further research is to be able to analyze the causes of the high product quality inconsistencies SMEs.

The Inconsistency Between The Notorious Jumping Frog of Calaveras County and The Man That Corrupted Hadleyburg

This paper compares Mark Twain’s The Notorious Jumping Frog of Calaveras County and The Man That Corrupted Hadleyburg,in terms of their stylistic and semantic inconsistency,specifically,their narrative technique and moral vision.

Is inconsistency of α-fetoprotein level a good prognosticator for hepatocellular carcinoma recurrence?

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.

Discrete Event System Framework for Fault Diagnosis with Measurement Inconsistency:Case Study of Rogue DHCP Attack

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.

SemID: Blind Image Inpainting with Semantic Inconsistency Detection

Most existing image inpainting methods aim to fill in the missing content in the inside-hole region of the target image. However, the areas to be restored in realistically degraded images are unspecified. Previous studies have failed to recover the degradations due to the absence of the explicit mask indication. Meanwhile, inconsistent patterns are blended complexly with the image content. Therefore, estimating whether certain pixels are out of distribution and considering whether the object is consistent with the context is necessary. Motivated by these observations, a two-stage blind image inpainting network, which utilizes global semantic features of the image to locate semantically inconsistent regions and then generates reasonable content in the areas, is proposed. Specifically, the representation differences between inconsistent and available content are first amplified, iteratively predicting the region to be restored from coarse to fine. A confidence-driven inpainting network based on prediction masks is then used to estimate the information regarding missing regions. Furthermore, a multiscale contextual aggregation module is introduced for spatial feature transfer to refine the generated contents. Extensive experiments over multiple datasets demonstrate that the proposed method can generate visually plausible and structurally complete results that are particularly effective in recovering diverse degraded images.

Lithium-ion cell inconsistency analysis based on three-parameter Weibull probability model

The inconsistency of lithium-ion cells degrades battery performance,lifetime and even safety.The complexity of the cell reaction mechanism causes an irregular asymmetrical distribution of various cell parameters,such as capacity and internal resistance,among others.In this study,the Newman electrochemical model was used to simulate the 1 C discharge curves of 100 LiMn2 O4 pouch cells with parameter variations typically produced in manufacturing processes,and the three-parameter Weibull probability model was used to analyze the dispersion and symmetry of the resulting discharge voltage distributions.The results showed that the dispersion of the voltage distribution was related to the rate of decrease in the discharge voltage,and the symmetry was related to the change in the rate of voltage decrease.The effect of the cells’capacity dominated the voltage distribution thermodynamically during discharge,and the phase transformation process significantly skewed the voltage distribution.The effects of the ohmic drop and polarization voltage on the voltage distribution were primarily kinetic.The presence of current returned the right-skewed voltage distribution caused by phase transformation to a more symmetrical distribution.Thus,the Weibull parameters elucidated the electrochemical behavior during the discharge process,and this method can guide the prediction and control of cell inconsistency,as well as detection and control strategies for cell management systems.

RESTlogic: Detecting Logic Vulnerabilities in Cloud REST APIs

logical testing model and resource lifecycle information,generate test cases and complete parameters,and alleviate inconsistency issues through parameter inference.Once again,we propose a method of analyzing test results using joint state codes and call stack information,which compensates for the shortcomings of traditional analysis methods.We will apply our method to testing REST services,including OpenStack,an open source cloud operating platform for experimental evaluation.We have found a series of inconsistencies,known vulnerabilities,and new unknown logical defects.

On the Proof of the Contradiction of Set Theory

The article is devoted to proving the inconsistency of set theory arising from the existence of strange trees. All steps of the proof rely on common informal set-theoretic reasoning, but they take into account the prohibitions that were introduced into axiomatic set theories in order to overcome the difficulties encountered by the naive Cantor set theory. Therefore, in fact, the article is about proving the inconsistency of existing axiomatic set theories, in particular, the ZFC theory.

Joint Estimation of Inconsistency and State of Health for Series Battery Packs

Battery packs are applied in various areas(e.g.,electric vehicles,energy storage,space,mining,etc.),which requires the state of health(SOH)to be accurately estimated.Inconsistency,also known as cell variation,is considered a significant evaluation index that greatly affects the degradation of battery pack.This paper proposes a novel joint inconsistency and SOH estimation method under cycling,which fills the gap of joint estimation based on the fast-charging process for electric vehicles.First,fifteen features are extracted from current change points during the partial charging process.Then,a joint estimation system is designed,where fusion weights are obtained by the analytic hierarchy process and multi-scale sample entropy to evaluate inconsistency.A wrapper is used to select the optimal feature subset,and Gaussian process regression is implemented to estimate the SOH.Finally,the estimation performance is assessed by the test data.The results show that the inconsistency evaluation can reflect the aging conditions,and the inconsistency does affect the aging process.The wrapper selection method improves the accuracy of SOH estimation by about 75.8%compared to the traditional filter method when only 10%of data is used for model training.The maximum absolute error and root mean square error are 2.58%and 0.93%,respectively.

Tableau Systems for Paraconsistency and Minimal Inconsistency

In this paper, the sematics of a paraconsistent logic and its nonmonotonic extension by minimal inconsistency are presented first. And then signed tableaux for paraconsistelit logic and minimal tableaux for logic of minimal inconsistency is proposetl. Finally the reduction of logic of paraconsistency and minimal inconsistency on ordinary semantics which provides new approach to proof procedure and implementation of paraconsistency and minimal inconsistency are provided.

What Caused the Inconsistency between Rb-Sr and^(40)Ar-^(39)Ar Ages of Authigenic Illites?

Radiogenic isotope dating of illitic clays has been widely used to reconstruct thermal and fluid flow events in siliciclastic sedimentary basins,the information of which is critical to investigate mechanisms of hydrocarbon maturation.This study carried out Rb-Sr and^(40)Ar-^(39)Ar dating of authigenic illitic clay samples separated from the Palaeogene sandstone in the northern South China Sea.Our Rb-Sr data further confirm the previously reported three periods of fluid flow events(at 34.5±0.9,31.2±0.6,and 23.6±0.8 Ma,respectively)in the northern South China Sea,which are related to regional episodic tectonism.However,^(40)Ar-^(39)Ar ages of illite obtained in this study are significantly younger than the corresponding Rb-Sr ages.The significantly younger^(40)Ar-^(39)Ar ages were probably due to ^(40)Ar loss caused by later dry heating events on the Hainan Island that have not affected the Rb-Sr isotopic systematics.The inconsistency between Rb-Sr and^(40)Ar-^(39)Ar data should be attributed to different isotopic behaviors of K-Ar and Rb-Sr isotopic systematics in illite.Our results indicate that Rb-Sr isotopic dating method may be a preferential approach for clay dating in geological settings where exist younger dry heating events.

Neural symbolic reasoning with knowledge graphs:Knowledge extraction,relational reasoning,and inconsistency checking

Knowledge graphs(KGs)express relationships between entity pairs,and many real-life problems can be formulated as knowledge graph reasoning(KGR).Conventional approaches to KGR have achieved promising performance but still have some drawbacks.On the one hand,most KGR methods focus only on one phase of the KG lifecycle,such as KG completion or refinement,while ignoring reasoning over other stages,such as KG extraction.On the other hand,traditional KGR methods,broadly categorized as symbolic and neural,are unable to balance both scalability and interpretability.To resolve these two problems,we take a more comprehensive perspective of KGR with regard to the whole KG lifecycle,including KG extraction,completion,and refinement,which correspond to three subtasks:knowledge extraction,relational reasoning,and inconsistency checking.In addition,we propose the implementation of KGR using a novel neural symbolic framework,with regard to both scalability and interpretability.Experimental results demonstrate that our proposed methods outperform traditional neural symbolic models.