Selection of control structure for distributed model predictive control in the presence of model errors

This paper presents a new methodology for selecting control structure in the context of distributed model predictive control. An index was developed to quantify the performance of distributed MPC strategies in the presence of model errors. This index was used for two purposes: to solve the decomposition problem whereby the process is decomposed into parts and to compare distributed MPC strategies with different degrees of coordination. Then, a multi-objective Mixed Integer Nonlinear Programming MINLP formulation is proposed to achieve an optimal trade-off between performance and structure simplicity.Four examples are considered to illustrate the methodology. The simulation results are consistent with the conclusions obtained from the analysis. The proposed methodology can be applied at the design stage to select the best control configuration in the presence of model errors.     

Window Query Processing in Linear Quadtrees

The linear quadtree is a spatial access method that is built by decomposing the spatial objects in a database into quadtree blocks and storing these quadtree blocks in a B-tree. The linear quadtree is very useful for geographic information systems because it provides good query performance while using existing B-tree implementations. An algorithm and a cost model are presented for processing window queries in linear quadtrees. The algorithm can handle query windows of any shape in the general case of spatial databases with overlapping objects. The algorithm recursively decomposes the space into quadtree blocks, and uses the quadtree blocks overlapping the query window to search the B-tree. The cost model estimates the I/O cost of processing window queries using the algorithm. The cost model is also based on a recursive decomposition of the space, and it uses very simple parameters that can easily be maintained in the database catalog. Experiments with real and synthetic data sets verify the accuracy of the cost model.     

Breaking the curse of dimensionality: hierarchical Bayesian network model for multi-view clustering

Annals of Mathematics and Artificial Intelligence - Clustering high-dimensional data under the curse of dimensionality is an arduous task in many applications domains. The wide dimension yields the...     

A survey of recursive analysis and Moore’s notion of real computation

The theory of analog computation aims at modeling computational systems that evolve in a continuous space. Unlike the situation with the discrete setting there is no unified theory of analog computation. There are several proposed theories, some of them seem quite orthogonal. Some theories can be considered as generalizations of the Turing machine theory and classical recursion theory. Among such are recursive analysis and Moore’s class of recursive real functions. Recursive analysis was introduced by Turing (Proc Lond Math Soc 2(42):230–265, 1936), Grzegorczyk (Fundam Math 42:168–202, 1955), and Lacombe (Compt Rend l’Acad Sci Paris 241:151–153, 1955). Real computation in this context is viewed as effective (in the sense of Turing machine theory) convergence of sequences of rational numbers. In 1996 Moore introduced a function algebra that captures his notion of real computation; it consists of some basic functions and their closure under composition, integration and zero-finding. Though this class is inherently unphysical, much work have been directed at stratifying, restricting, and comparing it with other theories of real computation such as recursive analysis and the GPAC. In this article we give a detailed exposition of recursive analysis and Moore’s class and the relationships between them.     

Beneficial Effects of Silicon (Si) on Sea Barley (Hordeum marinum Huds.) under Salt Stress

Silicon - Silicon (Si) plays an important role in providing beneficial effects on plant growth and yield, especially under stressful environments such as salinity. The objective of this work is to...     

Visual audience gatekeeping on social media platforms: A critical investigation on visual information diffusion before and during the Russo–Ukrainian War

Gatekeepers, including prerogative elites and institutions, possess multifaceted tools for controlling information. Historically, these gatekeepers have systematically instrumentalized visual information to shape audience perceptions in alignment with specific agendas. However, the advent of social media platforms has disrupted these power dynamics, empowering audiences through user-driven visual information exchanges. This has led to visual audience gatekeeping whereby users act as audience gatekeepers by selectively disseminating visual content, thus shaping information diffusion. While this democratisation of gatekeeping holds considerable promise for user empowerment, it also presents risks. These risks stem from the inherently persuasive yet manipulative qualities of visual content, compounded by users' susceptibility to unconscious biases, especially during polarising events. Therefore, we critically investigated visual audience gatekeeping in the context of the Russo–Ukrainian War, specifically focusing on a Reddit subforum devoted to Russia-related discussions. We find that visual audience gatekeeping operates within a paradigm that reflects the social reality the audience embraces. Audience gatekeepers disseminate visual information both to reproduce and defend an idealised conception of this social reality. Collectively, they produce a visual echo chamber characterised by low information diversity, which, in turn, reinforces and perpetuates the incumbent paradigm. However, heightened social tensions can trigger a paradigm shift and amplify the reproduction and defence processes, increasing the potential for the diffusion of more radical and extreme visual narratives. Based on our findings, we propose a theoretical model of visual audience gatekeeping, which has important implications for research on visuals, gatekeeping and social media platforms.     

Estimation of shale volume using a combination of the three porosity logs

An equation was developed for evaluating the volume of shale using standard porosity logs such as neutron, density and acoustic logs. The equation is written in terms of several parameters that are readily available from well-log measurements. This equation, which takes into consideration the effect of matrix, fluid and shale parameters, applies reasonably well for many shaly formations independent of the distribution of shales. The results demonstrate the applicability of the equation to well-log interpretation as a procedure for computing shale volume in shaly sand sedimentary sections.Three key advantages of the proposed equation are: (1) it incorporates several parameters that directly or indirectly affect the determination of shale in one equation, (2) it integrates the three porosity tools for a more accurate determination, and (3) it works well in hydrocarbon-bearing formations and where radioactive material other than shale is present.Successful application of the equation to shaly sand reservoirs is illustrated by analyses of samples from the Gulf of Suez.     

Implicitly Heterogeneous Multi-Stage Programming

Previous work on semantics-based multi-stage programming (MSP) language design focused on homogeneous designs, where the generating and the generated languages are the same. Homogeneous designs simply add a hygienic quasi-quotation and evaluation mechanism to a base language. An apparent disadvantage of this approach is that the programmer is bound to both the expressivity and performance characteristics of the base language. This paper proposes a practical means to avoid this by providing specialized translations from subsets of the base language to different target languages. This approach preserves the homogeneous “look” of multi-stage programs, and, more importantly, the static guarantees about the generated code. In addition, compared to an explicitly heterogeneous approach, it promotes reuse of generator source code and systematic exploration of the performance characteristics of the target languages. To illustrate the proposed approach, we design and implement a translation to a subset of C suitable for numerical computation, and show that it preserves static typing. The translation is implemented, and evaluated with several benchmarks. The implementation is available in the online distribution of MetaOCaml.     

Routing of Uncertain Traffic Demands

Due to the success of the Internet and the diversity of communication applications, it is becoming increasingly difficult to forecast traffic patterns. To capture the traffic variations, we introduce a flexible model where traffic belongs to a polytope. We assume that the traffic demands between nodes can be carried on many paths, with respect to network resources. Moreover, to guarantee the network stability and to make the routing easy to implement, the proportions of traffic flowing through each path have to be independent of the current traffic demands. We show that a minimum-cost routing satisfying the previous properties can be efficiently computed by column and constraint generations. We then present several strategies related to certain algorithmic details. Finally, theoretical and computational studies show that this new flexible model can be much more economical than a classical deterministic model based on a given traffic matrix. This paper can be considered as a mathematical framework for a new flexible virtual private network service offer. It also introduces a new concept: the routing of a polytope.This work was done in part while the authors were working at France Telecom Research and Development, Issy-les-Moulineaux, France.