Decoding the inconsistency of six cropland maps in China

Accurate cropland information is critical for agricultural planning and production,especially in foodstressed countries like China.Although widely used medium-to-high-resolution satellite-based cropland maps have been developed from various remotely sensed data sources over the past few decades,considerable discrepancies exist among these products both in total area and in spatial distribution of croplands,impeding further applications of these datasets.The factors influencing their inconsistency are also unknown.In this study,we evaluated the consistency and accuracy of six cropland maps widely used in China in circa 2020,including three state-of-the-art 10-m products(i.e.,Google Dynamic World,ESRI Land Cover,and ESA WorldCover)and three 30-m ones(i.e.,GLC_FCS30,GlobeLand 30,and CLCD).We also investigated the effects of landscape fragmentation,climate,and agricultural management.Validation using a ground-truth sample revealed that the 10-m-resolution WorldCover provided the highest accuracy(92.3%).These maps collectively overestimated Chinese cropland area by up to 56%.Up to 37%of the land showed spatial inconsistency among the maps,concentrated mainly in mountainous regions and attributed to the varying accuracy of cropland maps,cropland fragmentation and management practices such as irrigation.Our work shed light on the promotion of future cropland mapping efforts,especially in highly inconsistent regions.

Identifying Brand Consistency by Product Differentiation Using CNN

This paper presents a new method of using a convolutional neural network(CNN)in machine learning to identify brand consistency by product appearance variation.In Experiment 1,we collected fifty mouse devices from the past thirty-five years from a renowned company to build a dataset consisting of product pictures with pre-defined design features of their appearance and functions.Results show that it is a challenge to distinguish periods for the subtle evolution of themouse devices with such traditionalmethods as time series analysis and principal component analysis(PCA).In Experiment 2,we applied deep learning to predict the extent to which the product appearance variation ofmouse devices of various brands.The investigation collected 6,042 images ofmouse devices and divided theminto the Early Stage and the Late Stage.Results show the highest accuracy of 81.4%with the CNNmodel,and the evaluation score of brand style consistency is 0.36,implying that the brand consistency score converted by the CNN accuracy rate is not always perfect in the real world.The relationship between product appearance variation,brand style consistency,and evaluation score is beneficial for predicting new product styles and future product style roadmaps.In addition,the CNN heat maps highlight the critical areas of design features of different styles,providing alternative clues related to the blurred boundary.The study provides insights into practical problems for designers,manufacturers,and marketers in product design.It not only contributes to the scientific understanding of design development,but also provides industry professionals with practical tools and methods to improve the design process and maintain brand consistency.Designers can use these techniques to find features that influence brand style.Then,capture these features as innovative design elements and maintain core brand values.

Cross-Modal Consistency with Aesthetic Similarity for Multimodal False Information Detection

With the explosive growth of false information on social media platforms, the automatic detection of multimodalfalse information has received increasing attention. Recent research has significantly contributed to multimodalinformation exchange and fusion, with many methods attempting to integrate unimodal features to generatemultimodal news representations. However, they still need to fully explore the hierarchical and complex semanticcorrelations between different modal contents, severely limiting their performance detecting multimodal falseinformation. This work proposes a two-stage detection framework for multimodal false information detection,called ASMFD, which is based on image aesthetic similarity to segment and explores the consistency andinconsistency features of images and texts. Specifically, we first use the Contrastive Language-Image Pre-training(CLIP) model to learn the relationship between text and images through label awareness and train an imageaesthetic attribute scorer using an aesthetic attribute dataset. Then, we calculate the aesthetic similarity betweenthe image and related images and use this similarity as a threshold to divide the multimodal correlation matrixinto consistency and inconsistencymatrices. Finally, the fusionmodule is designed to identify essential features fordetectingmultimodal false information. In extensive experiments on four datasets, the performance of the ASMFDis superior to state-of-the-art baseline methods.

Adaptive Graph Embedding With Consistency and Specificity for Domain Adaptation

Domain adaptation(DA) aims to find a subspace,where the discrepancies between the source and target domains are reduced. Based on this subspace, the classifier trained by the labeled source samples can classify unlabeled target samples well.Existing approaches leverage Graph Embedding Learning to explore such a subspace. Unfortunately, due to 1) the interaction of the consistency and specificity between samples, and 2) the joint impact of the degenerated features and incorrect labels in the samples, the existing approaches might assign unsuitable similarity, which restricts their performance. In this paper, we propose an approach called adaptive graph embedding with consistency and specificity(AGE-CS) to cope with these issues. AGE-CS consists of two methods, i.e., graph embedding with consistency and specificity(GECS), and adaptive graph embedding(AGE).GECS jointly learns the similarity of samples under the geometric distance and semantic similarity metrics, while AGE adaptively adjusts the relative importance between the geometric distance and semantic similarity during the iterations. By AGE-CS,the neighborhood samples with the same label are rewarded,while the neighborhood samples with different labels are punished. As a result, compact structures are preserved, and advanced performance is achieved. Extensive experiments on five benchmark datasets demonstrate that the proposed method performs better than other Graph Embedding methods.

A Data Consistency Insurance Method for Smart Contract

As one of the major threats to the current DeFi(Decentralized Finance)ecosystem,reentrant attack induces data inconsistency of the victim smart contract,enabling attackers to steal on-chain assets from DeFi projects,which could terribly do harm to the confidence of the blockchain investors.However,protecting DeFi projects from the reentrant attack is very difficult,since generating a call loop within the highly automatic DeFi ecosystem could be very practicable.Existing researchers mainly focus on the detection of the reentrant vulnerabilities in the code testing,and no method could promise the non-existent of reentrant vulnerabilities.In this paper,we introduce the database lock mechanism to isolate the correlated smart contract states from other operations in the same contract,so that we can prevent the attackers from abusing the inconsistent smart contract state.Compared to the existing resolutions of front-running,code audit,andmodifier,our method guarantees protection resultswith better flexibility.And we further evaluate our method on a number of de facto reentrant attacks observed from Etherscan.The results prove that our method could efficiently prevent the reentrant attack with less running cost.

Asymptotic Consistency of the James-Stein Shrinkage Estimator

The study explores the asymptotic consistency of the James-Stein shrinkage estimator obtained by shrinking a maximum likelihood estimator. We use Hansen’s approach to show that the James-Stein shrinkage estimator converges asymptotically to some multivariate normal distribution with shrinkage effect values. We establish that the rate of convergence is of order and rate , hence the James-Stein shrinkage estimator is -consistent. Then visualise its consistency by studying the asymptotic behaviour using simulating plots in R for the mean squared error of the maximum likelihood estimator and the shrinkage estimator. The latter graphically shows lower mean squared error as compared to that of the maximum likelihood estimator.

On the Principle of Consistency of Rights and Obligations in the Constitution of PRC

“The Fundamental Rights and obligations of Citizens”, the title of Chapter II of the current Constitution of PRC, and the stipulation that citizens must fulfill certain obligations while enjoying rights have triggered many debates. Considering the historical origin, constitutional philosophy, and the text and structure of the Constitution, the special provisions of the current Constitution are influenced by the principle of consistency of rights and obligations. The principle of consistency of rights and obligations in the Constitution is of complex connotation. Therefore, although the principle of consistency of rights and obligations effectively connects the public and private spheres, it ignores the diversity and differences of the interests and elements contained in the Constitution, the asymmetry of the normative status of fundamental rights and fundamental obligations,and the right of citizens to self-determination of personal interests.The principle of consistency of rights and obligations should be purposefully narrowed and concretized: In the context of public-private integration and risk society prevention, the principle of consistency of rights and obligations can be used as a supplement to the functional system of the Constitution;in the field of fundamental political obligations, the principle of consistency of rights and obligations should be in line with the requirements of the state to respect and protect human rights;in the field of fundamental social obligations, the exercise of fundamental rights by individuals is protected by the Constitution as long as they comply with the law and do not infringe upon the interests of the social community. The principle of the consistency of rights and obligations is only used as the negative constituents of the determination of rights and the basis for the effect against a third party of fundamental rights.

On the Inconsistency of Classical Propositional Calculus

The classical propositional calculus(often called also as“zero-order logic”),is the most fundamental two-valued logical system.It is necessary to construct the classical calculus of quantifiers(often called also as“classical calculus of predicates”or“first-order logic”),which is necessary to construct the classical functional calculus.This last one is being used for formalization of the Arithmetic System.At the beginning of this paper,we introduce a notation and we repeat certain well-known notions(among others,the notions of operation of consequence,a system,consistency in the traditional sense,consistency in the absolute sense)and certain well-known theorems.Next,we establish that classical propositional calculus is an inconsistent theory.

CONSISTENCY OF MLE OF THE PARAMETER OF EXPONENTIAL LIFETIME DISTRIBUTION FOR RANDOM CENSORING MODEL WITH INCOMPLETE INFORMATION

In this paper, we have discussed a random censoring test with incomplete information, and proved that the maximum likelihood estimator(MLE) of the parameter based on the randomly censored data with incomplete information in the case of the exponential distribution has the strong consistency.

CONSISTENCY OF LS ESTIMATOR IN SIMPLE LINEAR EV REGRESSION MODELS

Consistency of LS estimate of simple linear EV model is studied. It is shown that under some common assumptions of the model, both weak and strong consistency of the estimate are equivalent but it is not so for quadratic-mean consistency.

Image segmentation by level set evolution with region consistency constraint

Image segmentation is a key and fundamental problem in image processing,computer graphics,and computer vision.Level set based method for image segmentation is used widely for its topology flexibility and proper mathematical formulation.However,poor performance of existing level set models on noisy images and weak boundary limit its application in image segmentation.In this paper,we present a region consistency constraint term to measure the regional consistency on both sides of the boundary,this term defines the boundary of the image within a range,and hence increases the stability of the level set model.The term can make existing level set models significantly improve the efficiency of the algorithms on segmenting images with noise and weak boundary.Furthermore,this constraint term can make edge-based level set model overcome the defect of sensitivity to the initial contour.The experimental results show that our algorithm is efficient for image segmentation and outperform the existing state-of-art methods regarding images with noise and weak boundary.

On consistency of the weighted arithmetical mean complex judgement matrix

The weighted arithmetical mean complex judgement matrix （WAMCJM） is the most common method for aggregating group opinions, but it has a shortcoming, namely the WAMCJM of the perfectly consistent judgement matrices given by experts canot guarantee its perfect consistency. An upper bound of the WAMCJM＇s consistency is presented. Simultaneously, a compatibility index of judging the aggregating extent of group opinions is also introduced. The WAMCJM is of acceptable consistency and is proved provided the compatibilities of all judgement matrices given by experts are smaller than the threshold value of acceptable consistency. These conclusions are important to group decision making.

Consistency check of degradation mechanism between natural storage and enhancement test for missile servo system

Reliability enhancement testing(RET) is an accelerated testing which hastens the performance degradation process to surface its inherent defects of design and manufacture. It is an important hypothesis that the degradation mechanism of the RET is the same as the one of the normal stress condition. In order to check the consistency of two mechanisms, we conduct two enhancement tests with a missile servo system as an object of the study, and preprocess two sets of test data to establish the accelerated degradation models regarding the temperature change rate that is assumed to be the main applied stress of the servo system during the natural storage. Based on the accelerated degradation models and natural storage profile of the servo system, we provide and demonstrate a procedure to check the consistency of two mechanisms by checking the correlation and difference of two sets of degradation data. The results indicate that the two degradation mechanisms are significantly consistent with each other.

THE CONSISTENCY AND ASYMPTOTIC NORMALITY OF NEAREST NEIGHBOR DENSITY ESTIMATOR UNDER α-MIXING CONDITION

We investigate the consistency and asymptotic normality of nearest-neighbor density estimator of a sample data process based on α-mixing assumption. We extend the correspondent result under independent identical cases.

HPLC Fingerprint with Multi-components Analysis for Quality Consistency Evaluation of Traditional Chinese Medicine Si-Mo-Tang Oral Liquid Preparation

Si-Mo-Tang（SMT） oral liquid preparation, a traditional Chinese medicine, was prepared from four crude herbal drugs, Fructus Aurantii Submaturus, Radix Aucklandiae, Semen Arecae and Radix Linderae Aggregatae. A combinative method using HPLC fingerprint and quantitative analysis was developed and validated for quality consistency evaluation of SMT. Individual HPLC chromatograms were evaluated against the mean chromatogram generated via a similarity evaluation computer program. Data from chromatographic fingerprints were also processed with principal component analysis（PCA） and hierarchical cluster analysis（HCA）. Additionally, six components （naringin, isonaringin, hesperidin, neohesperidin, norisoboldine and potassium sorbate） in SMT were simultaneously determined to interpret the quality consistency. For fingerprint analysis, 20 peaks were selected as the characteristic peaks to evaluate the similarities of 26 SMT collected from different manufacturers. Among the 20 characteristic peaks, 10 peaks were assigned to be naringin, hesperidin, neohesperidin, isonaringin, neoeriocitrin, tangeretin, nobiletin, norisoboldine, 5-（ethoxymethyl）furan-2-carbaldehyde and potassium sorbate, respectively. The results of similarity analysis, PCA and HCA, indicate that the samples from different manufacturers were consistent with each other in composition. The results from the quantitative data show that the contents of six compounds were significantly different in SMT oral liquid preparations from different manufacturers. The combinative method of chromatographic fingerprint with quantitative analysis developed here offered an efficient way for the quality consistency evaluation of the traditional Chinese medicine SMT.

Research on Key Issues of Consistency Analysis of Vehicle Steering Characteristics

Given the global lack of effective analysis methods for the impact of design parameter tolerance on performance deviation in the vehicle proof-of-concept stage,it is difficult to decompose performance tolerance to design parameter tolerance.This study proposes a set of consistency analysis methods for vehicle steering performance.The process of consistency analysis and control of automotive performance in the conceptual design phase is proposed for the first time.A vehicle dynamics model is constructed,and the multi-objective optimization software Isight is used to optimize the steering performance of the car.Sensitivity analysis is used to optimize the design performance value.The tolerance interval of the performance is obtained by comparing the original car performance value with the optimized value.With the help of layer-by-layer decomposition theory and interval mathematics,automotive performance tolerance has been decomposed into design parameter tolerance.Through simulation and real vehicle experiments,the validity of the consistency analysis and control method presented in this paper are verified.The decomposition from parameter tolerance to performance tolerance can be achieved at the conceptual design stage.

Behavior Consistency Computation for Workflow Nets With Unknown Correspondence

Consistency degree calculation is established on the basis of known correspondence, but in real life, the correspondence is generally unknown, so how to calculate consistency of two models under unknown correspondence has become a problem. For this condition, we should analyze unknown correspondence due to the influence of different correspondences.In this paper we obtain the relations of transitions based on event relations using branching processes, and build a behavioral matrix of relations. Based on the permutation of behavioral matrix, we express different correspondences, and define a new formula to compute the maximal consistency degree of two workflow nets. Additionally, this paper utilizes an example to show these definitions, computation as well as the advantages.

Consistency and Asymptotic Normality of MLE of Parameter Vector in a Randomly Censored GLM with Incomplete Information

The generalized linear model（GLM） based on the observed data with incomplete information in the case of random censorship is defined. Under the given conditions, the existence and uniqueness of the solution on the likelihood equations with respect to the parameter vector β of the model are discussed, and the consistency and asymptotic normality of the maximum likelihood estimator（MLE） βn^-, are proved.

Video Inter-Frame Forgery Identification Based on Consistency of Correlation Coefficients of Gray Values

Identifying inter-frame forgery is a hot topic in video forensics. In this paper, we propose a method based on the assumption that the correlation coefficients of gray values is consistent in an original video, while in forgeries the consistency will be destroyed. We first extract the consistency of correlation coefficients of gray values (CCCoGV for short) after normalization and quantization as distinguishing feature to identify interframe forgeries. Then we test the CCCoGV in a large database with the help of SVM (Support Vector Machine). Experimental results show that the proposed method is efficient in classifying original videos and forgeries. Furthermore, the proposed method performs also pretty well in classifying frame insertion and frame deletion forgeries.

Distributed model predictive control for multiagent systems with improved consistency

This paper addresses an improved distributed model predictive control （DMPC） scheme for multiagent systems with an attempt to improving its consistency. The deviation between what an agent is actually doing and what its neighbors believe that agent is doing is penalized in the cost function of each agent. At each sampling instant the compatibility constraint of each agent is set tighter than the previous sampling instant. Like the traditional approach, the performance cost is utilized as the Lyapunov function to prove closed-looped stability. The closed-loop stability is guaranteed if the weight matrix for deviation in the cost function are sufficiently large. The proposed distributed control scheme is formulated as quadratic programming with quadratic constraints. A numerical example is given to illustrate the effectiveness of the proposed scheme.