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The phenomena with within-strata characteristics that are more similar than between-strata characteristics are ubiquitous (e.g., land-use types and image classifications). It can be summarized as spatial stratified heterogeneity (SSH), which is measured and attributed using the geographical detector (Geodetector) q-statistic. SSH is typically calibrated by stratification and hundreds of algorithms have been developed. Little is discussed about the conditions of the methods. In this work, a novel stratification method based on head/tail breaks is introduced for the purpose of better capturing the SSH of geographical variables with a heavy-tailed distribution. Compared to conventional sample-based stratifications, the presented approach is a population-based optimized stratification that indicates an underlying scaling property in geographical spaces. It requires no prior knowledge or auxiliary variables and supports a naturally determined number of strata instead of being subjectively preset. In addition, our approach reveals the inherent hierarchical structure of geographical variables, characterizes its dominant components across all scales, and provides the potential to make the stratification meaningful and interpretable. The advantages were illustrated by several case studies in natural and social sciences. The proposed approach is versatile and flexible so that it can be applied for the stratification of both geographical and nongeographical variables and is conducive to advancing SSH-related studies as well. This study provides a new way of thinking for advocating spatial heterogeneity or scaling law and advances our understanding of geographical phenomena. [ABSTRACT FROM AUTHOR]

Socio-cyber-physical systems (SCPSs) have emerged as networked heterogeneous systems that incorporate social components (e.g., business processes and social networks) along with physical (e.g., Internet-of-Things devices) and software components. Model-driven techniques for building SCPSs need actor and goal models to capture social concerns, whereas system issues are often addressed with the Systems Modeling Language (SysML). Comprehensive traceability between these types of models is essential to support consistency and completeness checks, change management, and impact analysis. However, traceability management between these complementary views is not well supported across SysML tools, particularly when models evolve because SysML does not provide sophisticated out-of-the-box goal modeling capabilities. In our previous work, we proposed a model-based framework, called CGS4Adaptation, that supports basic traceability by importing goal and SysML models into a leading third-party requirement-management system, namely IBM Rational DOORS. In this paper, we present the framework's traceability management method and its use for automated consistency and completeness checks. Traceability management also includes implicit link detection, thereby, improving the quality of traceability links while better aligning designs with requirements. The method is evaluated using an adaptive SCPS case study involving an IoT-based smart home. The results suggest that the tool-supported method is effective and useful in supporting the traceability management process involving complex goal and SysML models in one environment while saving development time and effort. [ABSTRACT FROM AUTHOR]

We establish a theorem called the PCL theorem, which states that it is impossible to design a transactional memory algorithm that ensures (1) parallelism, i.e., transactions do not need to synchronize unless they access the same application objects, (2) very little consistency, i.e., a consistency condition, called weak adaptive consistency, introduced here and that is weaker than snapshot isolation, processor consistency, and any other consistency condition stronger than them (such as opacity, serializability, causal serializability, etc.), and (3) very little liveness, i.e., which transactions eventually commit if they run solo. [ABSTRACT FROM AUTHOR]

The development of imaging technology has allowed people to move beyond the black-and-white era and into the age of color. However, preserved black-and-white historical footage remains a precious memory for people. We propose a coloring method for historical videos that combines historical image coloring methods with temporal consistency methods, thus achieving color editing for historical videos. The temporal consistency technique uses deep video priors to model the video structure and effectively ensure smoothness between frames after video color editing, even with a small amount of training data. Meanwhile, we have collected a historical video dataset named MHMD-Video, which facilitates further research on colorization of historical videos for researchers. Finally, we demonstrate the effectiveness of the proposed method through objective and subjective evaluation. [ABSTRACT FROM AUTHOR]

Snapshot isolation (SI) is a widely used consistency model for transaction processing, implemented by most major databases and some of transactional memory systems. Unfortunately, its classical definition is given in a low-level operational way, by an idealised concurrency-control algorithm, and this complicates reasoning about the behaviour of applications running under SI. We give an alternative specification to SI that characterises it in terms of transactional dependency graphs of Adya et al., generalising serialisation graphs. Unlike previous work, our characterisation does not require adding additional information to dependency graphs about start and commit points of transactions. We then exploit our specification to obtain two kinds of static analyses. The first one checks when a set of transactions running under SI can be chopped into smaller pieces without introducing new behaviours, to improve performance. The other analysis checks whether a set of transactions running under a weakening of SI behaves the same as when running under SI. [ABSTRACT FROM AUTHOR]

When regression function belongs to Besov space, wavelet estimations are investigated by Chesneau and Shirazi (2014), Kou and Liu (2016, 2017). However, in many practical applications, one does not know whether the regression function is smooth or not. It makes sense to discuss consistency of wavelet estimator. This paper considers the mean LP(1 ≤ p ≤ ∞) consistency of wavelet estimator for multivariate regression functions based on biased data. [ABSTRACT FROM AUTHOR]

We show that neither Peleg's nor Tadenuma's well-known axiomatizations of the core by non-emptiness, individual rationality, super-additivity, and max consistency or complement consistency, respectively, hold when only convex rather than balanced TU games are considered, even if anonymity is required in addition. Moreover, we show that the core and its relative interior are the only two solutions that satisfy Peleg's axioms together with anonymity and converse max consistency on the domain of convex games. [ABSTRACT FROM AUTHOR]

Pairwise comparison is a useful tool to express decision makers' (DMs') preferences in the group decision-making (GDM) problems. However, the preferences provided by pairwise comparisons could be self-contradictory, i.e., ordinal inconsistencies exist. Therefore, before reaching consensus, the first thing is to assure the DM's judgments that are not contradictory. As the purpose of the GDM is to choose most preferred alternative, the consensus degree for each alternative of all the DMs should be measured. In the present paper, an alternative consensus model for additive preference relations (APRs) based on ordinal consistency (OC) is developed. An algorithm is applied to detect and adjust the ordinally inconsistent elements for APRs. Then the alternative rankings for each ordinally consistent APR and the aggregated APR is obtained, respectively. A model is designed to change the DMs' importance, which increases the alternative consensus degree. The proposed model does not change the DMs' preferences, aiming to make full use of the DMs' judgements. Finally, an illustrative example and comparisons with the current approaches are furnished to demonstrate the effectiveness of the developed method. [ABSTRACT FROM AUTHOR]

• SCDC is a novel cross-modal dictionary learning algorithm which can preserve the semantic consistency of different modalities in a latent space. Specially, we construct the undirected graph to learn an orthogonal space instead of utilizing the original semantic space. • SCDC takes into consideration l 21 -norm regularization and rank constraint simultaneously. It not only selects the discriminative features but also improves the correlation of different modalities. These two constraints are rarely seen together in the field of dictionary learning. • The proposed approach can be easily applied to other modalities. And experimental results demonstrate its effectiveness. Cross-modal retrieval develops rapidly due to the growth and widespread applications of multimodal data. How to reduce the heterogeneous gap and impose effective constraints on different modalities are two basic problems. In this paper, we propose a novel Semantic Consistency cross-modal Dictionary learning algorithm with rank Constraint (SCDC) to solve these aforementioned problems. An orthogonal space learned by spectral regression is introduced, in which different modalities can be measured directly. Specifically, images and texts are encoded by their dictionaries to obtain corresponding reconstruction coefficients. A l 21 -norm term is imposed on these coefficients in order to select discriminative features and avoid over-fitting simultaneously. In the meantime, a rank constraint is imposed on the transformed features so as to improve the correlation of different modalities. Experimental results on three popular datasets demonstrate that SCDC is significantly superior to several state-of-the-art methods. [ABSTRACT FROM AUTHOR]

The CAP theorem states that only two of these properties can be simultaneously guaranteed in a distributed service: (i) consistency, (ii) availability and (iii) network partition tolerance. This theorem was stated and proved assuming that 'consistency' refers to atomic consistency. However, multiple consistency models exist and atomic consistency is located at the strongest edge of that spectrum. Many distributed services deployed in cloud platforms should be highly available and scalable. Network partitions may arise in those deployments and should be tolerated. One way of dealing with CAP constraints consists in relaxing consistency. Therefore, it is interesting to explore the set of consistency models not supported in an available and partition-tolerant service (CAP-constrained models). Other weaker consistency models could be maintained when scalable services are deployed in partitionable systems (CAP-free models). Three contributions arise: (i) multiple other CAP-constrained models are identified, (ii) a borderline between CAP-constrained and CAP-free models is set and (iii) a hierarchy of consistency models depending on their strength and convergence is built. [ABSTRACT FROM AUTHOR]

Task-based runtime systems are seen as a way to deal with increasing heterogeneity and performance variability in modern high performance computing systems. The Open Community Runtime is an example of such runtime system, with the benefit of having an open specification that defines its interface and behavior. This allows others to study the design and create alternative implementations of the runtime system. However, it turns out that the consistency model that defines how the OCR programs are synchronized when executed in parallel is not sufficiently defined. In the following text, we complete the consistency model by filling in the missing pieces and extending the memory model given in the specification. [ABSTRACT FROM AUTHOR]

Abstract Motivated by an application in the context of experimental fatigue tests we study the problem of estimating conditional quantiles from data that contains additional measurement errors. The only assumption on these errors is that a weighted sum of the absolute errors tends to zero with probability one for sample size tending to infinity. We show that the plug-in quantile estimate corresponding to a local averaging estimate of the conditional distribution function (codf) approaches the quantile set asymptotically, presumed that the local averaging estimate of the codf is pointwise strongly consistent. We also investigate the rate of convergence and show that our plug-in estimate achieves at least the same pointwise rate of convergence as the local averaging estimate of the codf plus the square root of the weighted sum of the absolute errors. Finally, the results are applied in simulations and in the context of experimental fatigue tests. Highlights • Nonparametric quantile estimation of number of cycles in experimental fatigue tests. • Consistency result for quantile estimate based on data with measurement errors (ME). • Proof of rate of convergence for this quantile estimate based on data with ME. [ABSTRACT FROM AUTHOR]

Abstract Consistency is related with reasonableness. This paper proposes a graphical method to visualize and rectify different inconsistencies for fuzzy reciprocal preference relations (FPRs), and the consistency includes the ordinal and cardinal consistencies. Ordinal inconsistency implies cardinal inconsistency, but not vice versa, and cardinal consistency of FPRs includes additive consistency and multiplicative consistency. Therefore, there are four types of inconsistencies, includes: (1) the additive inconsistency; (2) the multiplicative inconsistency; (3) the ordinal and additive inconsistencies, and (4) the ordinal and multiplicative inconsistencies. First, Gower plots are proposed to visualize the ordinal and cardinal inconsistencies on a two-dimensional plane. Then, some optimization models are formulated to rectify the four different types of inconsistences, respectively. Some examples are illustrated to show how the models work, and comparisons with the existing methods are also offered to show the advantages of the proposed methods. [ABSTRACT FROM AUTHOR]

Abstract Models are extensively used in many areas of software engineering to represent the behaviour of software systems at different levels of abstraction. Because of the involvement of different stakeholders in constructing these models and their independent evolution, inconsistencies might occur between the models. It is thus crucial to detect these inconsistencies at early phases of the software development process, and especially as soon as refined models deviate from their abstract counterparts. In this article, we introduce a containment checking approach to verify whether a certain low-level behaviour model, typically created by refining and enhancing a high-level model, still is consistent with the specification provided in its high-level counterpart. We interpret the containment checking problem as a model checking problem, which has not received special treatment in the literature so far. Because the containment checking is based on model checking, it requires both formal consistency constraints and specifications of these models. Unfortunately, creating formal consistency constraints and specifications is currently done manually, and therefore, labour-intensive and error prone. To alleviate this issue, we define and develop a fully automated transformation of behaviour models into formal specifications and properties. The generated formal specifications and properties can directly be used by existing model checkers for detecting any discrepancy between the input models and yield corresponding counterexamples. Moreover, our approach can provide the developers more informative and comprehensive feedback regarding the inconsistency issues, and therefore, help them to efficiently identify and resolve the problems. The evaluation of various scenarios from industrial case studies demonstrates that the proposed approach efficiently translates the behaviour models into formal specifications and properties. Highlights • Containment checking of software behaviour models at different abstraction levels. • Automated transformation of models into LTL formulas and formal SMV descriptions. • Counterexample interpretation for resolving the inconsistencies between models. • Applicability and feasibility of the approach for realistically sized models. • Performance evaluation in a typical developer's working environment. [ABSTRACT FROM AUTHOR]

This paper is to propose an information management technique, which is easy to understand by humans and easy to utile analysis program, in order to manage complicated machines and facilities. To manage the facilities, we show a modeling that partly defines the structure of the facilities by set theory, further defines the requirements for joining the subset of structured identifiers on consistency. In verification of the proposal and programming method, we show how to control the amount of information of structured identifier as uniquely identifier. As a result, we show our proposal is useful to address real problems in management software. [ABSTRACT FROM AUTHOR]

The individual consistency and the consensus degree are two basic measures to conduct group decision making with reciprocal preference relations. The existing frameworks to manage individual consistency and consensus degree have been investigated intensively and follow a common resolution scheme composed by the two phases: the consistency improving process, and the consensus reaching process. But in these frameworks, the individual consistency will often be destroyed in the consensus reaching process, leading to repeat the consistency improving process, which is time consuming. In order to avoid repeating the consistency improving process, a consensus reaching process with individual consistency control is proposed in this paper. This novel consensus approach is based on the design of an optimization-based consensus rule, which can be used to determine the adjustment range of each preference value guaranteeing the individual consistency across the process. Finally, theoretical and numerical analysis are both used to justify the validity of our proposal. [ABSTRACT FROM AUTHOR]

Abstract In unstructured mobile peer-to-peer systems (MP2P), the frequent link breakages lead frequent topology mismatching problems and data transmission failures due to high mobility of nodes. The overhead of data transmission and synchronization cannot be neglected. In order to keep the data consistent, flooding is a fundamental and straightforward data synchronization mechanism since a mobile node does not know which else has the same shared data item. However, data flooding causes the broadcast storm problem. In this paper, we propose a mobility-aware data update approach (MADU) to improve the data dissemination and to reduce the overhead of maintaining the consistency of shared data items in an MP2P network. We use safe-time which is derived from the neighbor's location and speed to determine the time for a node to do the checking and updating between the neighbor nodes and itself. We also consider the network connectivity of a mobile node and access frequency of a data item as the factors to trigger the update process. By combining the mobility information of nodes, network connectivity, and access frequency of data items, we set a reasonable data update mechanism, which can significantly decrease the number of retransmissions and redundant messages so as to reduce the overhead of maintaining the data consistency. [ABSTRACT FROM AUTHOR]

Individual consistency and group consensus are important topics in group decision-making process with preference relations. This study introduces a programming model to meet the individual consistency level and group consensus threshold value simultaneously. First, the distance measure between two probabilistic hesitant fuzzy preferences (PHFPRs) is proposed, and a consistency index for PHFPR is defined based on the proposed distance measure. Then, a mathematical programming model is constructed to improve its consistency when the PHFPR does not meet the consistency level. Second, considering that some values in PHFPRs provided by the decision makers may be missing in the decision-making process, a mathematical programming model is constructed to derive the missing values. Third, the proximity degree between any two decision makers is proposed, and a consensus index among the decision makers is defined based on the proposed proximity degree. Then, a mathematical programming model is constructed to obtain the expected consistency level and consensus threshold value simultaneously. Finally, an example is provided to illustrate the effectiveness of the proposed method. Comparative studies with several existing methods are also provided. [ABSTRACT FROM AUTHOR]

Estimation of quality of expert judgements and their suitability for reliable evaluation of decision alternatives is one of key issues for successful decision-making. The notions of strong and weak consistency are used to estimate the contradiction level of expert pairwise comparison matrix (PCM). Several methods are used to find the most inconsistent elements of a PCM. They may lead to different results, and there is a problem to find an element that has to be changed to increase the consistency level of a PCM. To solve this problem, a novel methodology for analysis of efficiency of methods for finding the most inconsistent elements of a PCM is proposed. An improved M_Outflow method for finding the most inconsistent element and a cycle in a PCM is established. Using computer modelling, it is shown that the proposed M_Outflow method is more efficient under accepted conditions in comparison with other considered methods. [ABSTRACT FROM AUTHOR]

Summary: Energy conservation and consistency are not easy to achieve simultaneously in smoothed particle hydrodynamics (SPH). In this study, an efficient strategy is proposed to achieve energy conservation in an SPH framework with a consistent basis function. Herein, at every particle pair interaction, a correction term is introduced such that energy conservation is restored locally and, at the same time, the total variation of different variables due to the correction term is minimum. The final form of the proposed formulation is such that no additional computational effort is required and the simplicity of SPH is preserved. The theoretical error estimate of the proposed formulation is performed. The proposed scheme is also compared with benchmark SPH formulations in terms of the L2 error norm for representative functional derivatives both in regular and irregular particle distributions. Finally, the efficacy of the proposed formulation in conserving energy and maintaining accuracy is demonstrated via few elastic, elastic‐plastic impact and fracture problems. [ABSTRACT FROM AUTHOR]

Copyright of Ingénierie des Systèmes d'Information is the property of International Information & Engineering Technology Association (IIETA) and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Ingénierie des Systèmes d'Information is the property of International Information & Engineering Technology Association (IIETA) and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Time consistency is one of the most important properties of solutions in cooperative differential games. This paper uses the core as a cooperative solution of the game. We design a strong time-consistent subset of the core. The design method of this subset is based on a special class of imputation distribution procedures (IDPs). [ABSTRACT FROM AUTHOR]

Abstract: Human beings represent and process imperfect information in a natural way, whereas effective approaches are still being looked for in the area of soft computing. Atanassov's intuitionistic fuzzy sets and especially Atanassov's intuitionistic fuzzy relations are are tools that make it possible to model in an effective way imperfect information. In this paper, we discuss the transitivity problem of Atanassov's intuitionistic fuzzy relations. The transitivity property reflects the consistency of a preference relation. Therefore, transitivity is important from the point of view of real problems appearing, e.g., in group decision making, choice, and utility theories widely making use of the preference procedures. We study here in detail transitivity property of Atanassov's intuitionistic fuzzy relations and propose a new algorithm for generating weakly transitivity among the alternatives (options) considered. Next, making use of the new algorithm we propose a procedure of ranking of the alternatives in a group decision‐making problem. [ABSTRACT FROM AUTHOR]

Among the local consistency techniques used for solving constraint networks, path-consistency (PC) has received a great deal of attention. However, enforcing PC is computationally expensive and sometimes unnecessary. Directional PC (DPC) is a weaker notion of PC that considers a given variable ordering and can thus be enforced more efficiently than PC. This paper shows that (the DPC enforcing algorithm of Dechter and Pearl) decides the constraint satisfaction problem (CSP) of a constraint language if it is complete and has the variable elimination property (VEP). However, we also show that no complete VEP constraint language can have a domain with more than two values. We then present a simple variant of the algorithm, called, and show that the CSP of a constraint language can be decided by if it is closed under a majority operation. In fact, is sufficient for guaranteeing backtrack-free search for such constraint networks. Examples of majority-closed constraint classes include the classes of connected row-convex constraints and tree-preserving constraints, which have found applications in various domains, such as scene labeling, temporal reasoning, geometric reasoning and logical filtering. Our experimental evaluations show that significantly outperforms the state-of-the-art algorithms for solving majority-closed constraints. [ABSTRACT FROM AUTHOR]

Supervised learning has seen numerous theoretical and practical advances over the last few decades. However, its basic assumption of identical train and test distributions often fails to hold in practice. One important example of this is when the training instances are subject to label noise: that is, where the observed labels do not accurately reflect the underlying ground truth. While the impact of simple noise models has been extensively studied, relatively less attention has been paid to the practically relevant setting of instance-dependent label noise. It is thus unclear whether one can learn, both in theory and in practice, good models from data subject to such noise, with no access to clean labels. We provide a theoretical analysis of this issue, with three contributions. First, we prove that for instance-dependent (but label-independent) noise, any algorithm that is consistent for classification on the noisy distribution is also consistent on the noise-free distribution. Second, we prove that consistency also holds for the area under the ROC curve, assuming the noise scales (in a precise sense) with the inherent difficulty of an instance. Third, we show that the Isotron algorithm can efficiently and provably learn from noisy samples when the noise-free distribution is a generalised linear model. We empirically confirm our theoretical findings, which we hope may stimulate further analysis of this important learning setting. [ABSTRACT FROM AUTHOR]

The reasonable extraction and utilization of observation information are considered as the key of design and optimization of filters. By constructing the sampling steps of multi-sensor bootstrapped observations and the validation process of credible observations, a novel distributed Kalman filter in multi-sensor observations based on Metropolis-Hastings (M-H) sampling strategy is proposed in this paper. Firstly, combined with the latest observation information and the accuracy information of sensor which is also used to describe the prior modeling knowledge of observation system, we design the bootstrapped observation sampling for linear observation system. Secondly, aiming to the consistency deviation phenomenon appearing in the bootstrapped observations of single sensor, through constructing the likelihood degree of multi-sensor bootstrapped observations and the accept probability of credible observations, meanwhile, combined with the M-H sampling strategy, we give the validation method of credible observations. Finally, the realization steps of new algorithm are constructed according to the weighted fusion criterion. The advantage of new algorithm is to improve greatly the filtering precision with additional less hardware costs. The theoretical analysis and experimental results show the feasibility and efficiency of the proposed algorithm. [ABSTRACT FROM AUTHOR]

Suppose that we are given a time series where consecutive samples are believed to come from a probabilistic source, that the source changes from time to time and that the total number of sources is fixed. Our objective is to estimate the distributions of the sources. A standard approach to this problem is to model the data as a hidden Markov model (HMM). However, since the data often lacks the Markov or the stationarity properties of an HMM, one can ask whether this approach is still suitable or perhaps another approach is required. In this paper, we show that a maximum likelihood HMM estimator can be used to approximate the source distributions in a much larger class of models than HMMs. Specifically, we propose a natural and fairly general non-stationary model of the data, where the only restriction is that the sources do not change too often. Our main result shows that for this model, a maximum-likelihood HMM estimator produces the correct second moment of the data, and the results can be extended to higher moments. [ABSTRACT FROM AUTHOR]

Summary: Active probing is a widely adopted approach for developing effective solutions for network monitoring and diagnosing. However, the use of probing techniques incurs costs in terms of additional network traffic. Furthermore, probing stations are required to be configured and maintained in the network for sending out probes. The set of probes used for fault detection and/or diagnosis (called the target probe set) is selected by a probe selection algorithm from a larger set called the candidate probe set. Most of the existing techniques for selecting the target probe set assume that the candidate probe set will preexist and the set is determined by the configured routing model in the network. In this paper, we address the problem of generating an expanded candidate probe set, which results in the selection of a more efficient target probe set. We propose the use of heuristics and network partitioning strategies for generating the candidate probe set. For evaluating our approach, we perform experiments to generate candidate probe sets for the networks of several types and sizes. The candidate probe sets are used by the existing probe selection algorithms for selecting target probe sets for fault detection and localization. Our results demonstrate that the target probe set selected from the candidate probe set generated using our approach has a reduced cost of monitoring the network. [ABSTRACT FROM AUTHOR]

Possible world has shown to be effective for handling various types of data uncertainty in uncertain data management. However, few uncertain data clustering and classification algorithms are proposed based on possible world. Moreover, existing possible world based algorithms suffer from the following issues: (1) they deal with each possible world independently and ignore the consistency principle across different possible worlds; (2) they require the extra post-processing procedure to obtain the final result, which causes that the effectiveness highly relies on the post-processing method and the efficiency is also not very good. In this paper, we propose a novel possible world based consistency learning model for uncertain data, which can be extended both for clustering and classifying uncertain data. This model utilizes the consistency principle to learn a consensus affinity matrix for uncertain data, which can make full use of the information across different possible worlds and then improve the clustering and classification performance. Meanwhile, this model imposes a new rank constraint on the Laplacian matrix of the consensus affinity matrix, thereby ensuring that the number of connected components in the consensus affinity matrix is exactly equal to the number of classes. This also means that the clustering and classification results can be directly obtained without any post-processing procedure. Furthermore, for the clustering and classification tasks, we respectively derive the efficient optimization methods to solve the proposed model. Experimental results on real benchmark datasets and real world uncertain datasets show that the proposed model outperforms the state-of-the-art uncertain data clustering and classification algorithms in effectiveness and performs competitively in efficiency. [ABSTRACT FROM AUTHOR]

To solve the global optimization problem in heavy machinery, a multidisciplinary design optimization (MDO) computing environment is developed based on high level architecture (HLA). The computing environment encapsulates the analysis optimization tools in relevant disciplinary fields to seek global optimization design based on a single disciplinary optimization. The goal of a minimum discrepancy between the subsystem-level design variables and system-level target values is reached by establishing multidisciplinary consistency constraints. The HLA-compliant optimization model realizes collaboration and interoperation between the disciplines through mapping the coupled state variables to corresponding published or subscribed attributes of an object class according to the rules of HLA. Finally, an example application of designing a hydraulic-powered support is presented to demonstrate the effectiveness of the optimization environment. [ABSTRACT FROM AUTHOR]

Logic-based models have been already proposed for information retrieval purpose. However, there is a need for new formalisms providing more generic frameworks. For this purpose, an information retrieval axiomatic theory is proposed in this paper, independently of any model. Our proposal which mainly relies on many-sorted logic allows to consider various sets in the domain of discourse that provides us a rich framework to model the different items such as documents, index terms, queries. The theory relies on a sound set of axioms driving the retrieval process as proof of theorems. As such the genericity consists of a main motivation; it will be proved that three classical information retrieval models, namely the Boolean model; the fuzzy-set-based extension of the Boolean model; and the vector space model, satisfy the proposed theory, establishing then its consistency. Beyond the genericity, the proposed approach may face concrete problems. Indeed, it is well known that the use of the classical settings of formal concept analysis theory for information retrieval does not allow disjunctions and negations in queries. For this purpose, this paper gives a characterization of these queries forms using appropriates theorems of the theory. Useful algebraic properties (i.e., isomorphisms) are then established for this end. [ABSTRACT FROM AUTHOR]

O Chance corrected agreement coefficients such as the Cohen and Fleiss Kappas are commonly used for the measurement of consistency in the decisions made by clinical observers or raters. However, the way that they estimate the probability of agreement (Pe) or cost of disagreement (De) 'by chance' has been strongly questioned, and alternatives have been proposed, such as the Aickin Alpha coefficient and the Gwet AC1 and AC2 coefficients. A well known paradox illustrates deficiencies of the Kappa coefficients which may be remedied by scaling Pe or De according to the uniformity of the scoring. The AC1 and AC2 coefficients result from the application of this scaling to the Brennan-Prediger coefficient which may be considered a simplified form of Kappa. This paper examines some commonly used multi-rater agreement coefficients including AC1 and AC2. It then proposes an alternative subject-by-subject scaling approach that may be applied to weighted and unweighted multi-rater Cohen and Fleiss Kappas and also Intra-Class Correlation (ICC) coefficients. [ABSTRACT FROM AUTHOR]

In software development, models are often used to represent multiple views of the same system. Such models need to be properly related to each other in order to provide a consistent description of the developed system. Models may contain contradictory system specifications, for instance, when they evolve independently. Therefore, it is very crucial to ensure that models conform to each other. In this context, we focus on consistency checking of behavior models. Several techniques and approaches have been proposed in the existing literature to support behavioral model consistency checking. This article presents a Systematic Literature Review (SLR) that was carried out to obtain an overview of the various consistency concepts, problems, and solutions proposed regarding behavior models. In our study, the identification and selection of the primary studies was based on a well-planned search strategy. The search process identified a total of 1770 studies, out of which 96 have been thoroughly analyzed according to our predefined SLR protocol. The SLR aims to highlight the state-of-the-art of software behavior model consistency checking and identify potential gaps for future research. Based on research topics in selected studies, we have identified seven main categories: targeted software models, types of consistency checking, consistency checking techniques, inconsistency handling, type of study and evaluation, automation support, and practical impact. The findings of the systematic review also reveal suggestions for future research, such as improving the quality of study design and conducting evaluations, and application of research outcomes in industrial settings. For this purpose, appropriate strategy for inconsistency handling, better tool support for consistency checking and/or development tool integration should be considered in future studies. [ABSTRACT FROM AUTHOR]

Real-time collaborative graphical editing system allows a group of users simultaneously to view and edit the shared graphical documents from geographically dispersed sites connected by networks. The strategy of consistency maintenance is the key technique to ensure correctness in this editing system. This paper maps the two-dimensional drawing area into the linear structure in the real-time collaborative graphical editing system in the Web environment, and transforms the two-dimensional graphical operations to the linear operations. Based on the above, this paper improves the ABST algorithm to be suitable for this new environment. In order to verify the correctness and feasibility of the algorithm, this paper develops the real-time collaborative graphical editing system CoWebDraw based on Web, which adopts the HTML5 WebSocket protocol to achieve the real-time transformation of the information. In this system, geographically dispersed users can edit the shared graphical documents through web browsers. In the mobile internet era, the CoWebDraw system supports the concurrent editing of the same documents by multi-clients. [ABSTRACT FROM AUTHOR]

Establishing arc consistency on two relational structures is one of the most popular heuristics for the constraint satisfaction problem. We aim at determining the time complexity of arc consistency testing. The input structures G and H can be supposed to be connected colored graphs, as the general problem reduces to this particular case. We first observe the upper bound O ( e ( G ) v ( H ) + v ( G ) e ( H ) ) , which implies the bound O ( e ( G ) e ( H ) ) in terms of the number of edges and the bound O ( ( v ( G ) + v ( H ) ) 3 ) in terms of the number of vertices. We then show that both bounds are tight as long as an arc consistency algorithm is based on constraint propagation (as all current algorithms are). Our lower bounds are based on examples of slow constraint propagation. We measure the speed of constraint propagation observed on a pair G , H by the size of a combinatorial proof that Spoiler wins the existential 2-pebble game on G , H . [ABSTRACT FROM AUTHOR]

Visualizations often appear in multiples, either in a single display (e.g., small multiples, dashboard) or across time or space (e.g., slideshow, set of dashboards). However, existing visualization design guidelines typically focus on single rather than multiple views. Solely following these guidelines can lead to effective yet inconsistent views (e.g., the same field has different axes domains across charts), making interpretation slow and error-prone. Moreover, little is known how consistency balances with other design considerations, making it difficult to incorporate consistency mechanisms in visualization authoring software. We present a wizard-of-oz study in which we observed how Tableau users achieve and sacrifice consistency in an exploration-to-presentation visualization design scenario. We extend (from our prior work) a set of encoding-specific constraints defining consistency across multiple views. Using the constraints as a checklist in our study, we observed cases where participants spontaneously maintained consistent encodings and warned cases where consistency was overlooked. In response to the warnings, participants either revised views for consistency or stated why they thought consistency should be overwritten. We categorize participants' actions and responses as constraint validations and exceptions, depicting the relative importance of consistency and other design considerations under various circumstances (e.g., data cardinality, available encoding resources, chart layout). We discuss automatic consistency checking as a constraint-satisfaction problem and provide design implications for communicating inconsistencies to users. [ABSTRACT FROM PUBLISHER]

We consider a society whose members have to choose not only an outcome from a given set of outcomes but also a subset of agents that will remain members of the society. We study the extensions of approval voting, scoring methods and the Condorcet winner to our setting from the point of view of their internal stability and consistency properties. [ABSTRACT FROM AUTHOR]

Event processing is one of the cornerstone technologies in bridging physical world and cyber system together. Although event-based processing system has been widely used in various applications, however, consistency of event processing is still an open issue need further exploration. The inconsistency problem produces inaccurate detection result and corrupts the system correctness. In this paper, we propose a semantic approach for event modeling and detection model transformation with a semantic calculus system. Particularly, we first propose a complex event semantic model, OntoEvent, and define several key operators and properties to describe the logic, temporal and attribute relations in complex events. Second, we propose the concept of event constraint and elaborate the occurrence, temporal, and attribute functions to formalize the semantic implications in OntoEvent model. On that basis, we present the extraction rules and establish a calculus mechanism for constraints based on axioms. With these works, an automata-based detection model, named OntoCEP (Ontology-based Complex Event Detection), and a pipelined procedure for the assembly from constraints to OntoCEP model is proposed. The procedure is composed of several sequential phases and the consistency in each assembly phase is proved. Therefore, we establish a semantic-consistent mapping mechanism from event to detection model in the form of constraints. Experiments and evaluations prove that our approach ensure the consistency with event and detection models. Besides, our detection model consumes less computational resources and outperforms other selected benchmarked models in terms of computational efficiency and processing capability. [ABSTRACT FROM AUTHOR]

Quiescent consistency is a notion of correctness for a concurrent object that gives meaning the object's behaviour in its quiescent states. This paper shows that the membership problem for quiescent consistency is NP-complete and that the correctness problem is decidable, but coNEXPTIME-complete. We consider restricted versions of quiescent consistency by assuming an upper limit on the number of events between two quiescent points. Here, we show that the membership problem is in PTIME, whereas correctness is PSPACE-complete. We also consider quiescent sequential consistency, which strengthens quiescent consistency with an additional sequential consistency condition. We show that the unrestricted versions of membership and correctness are NP-complete and undecidable, respectively. When placing a limit on the number of events between two quiescent points, membership is in PTIME, while correctness is PSPACE-complete. Given an upper limit on the number of processes for every run of the implementation, the membership problem is in PTIME. [ABSTRACT FROM AUTHOR]

This paper studies the ordinal and additive consistency issues of fuzzy linguistic preference relations (FLPRs). First, a graphic method of Gower plot is proposed to ascertain ordinal and additive inconsistencies for FLPRs. Then, two optimization models are established to adjust the ordinal and additive inconsistencies at the same time. Furthermore, an approach based on Gower plot is developed to help the decision maker to improve the consistency and rank the alternatives which respects the views of decision makers with greatest degree. Finally, numerical examples and comparisons with the existing methods are furnished to show the effectiveness and advantages of the proposed method. [ABSTRACT FROM AUTHOR]