Air to Water Generator Integrated Systems: The Proposal of a Global Evaluation Index—GEI Formulation and Application Examples

Due to water scarcity, in the last few decades, air-to-water generator (AWG) technology, whose useful effect is the extraction of water from air, has been improved. In particular, in the last few years, advanced AWG integrated systems have been developed. Such systems permit, not only to condense water from air, but also the smart use of the by-side effects of the process in order to partially or totally cover the heating ventilation air conditioning (HVAC) needs of a building. Presently, there are no evaluation tools that permit a complete comparison among AWG machines, taking into account all the useful effects that can be obtained at the same time and with the same energy input. The current work, starting from the need for such a tool, proposes a global index whose formulation considers all useful effects of an integrated system, the energy required to obtain them, and the integration degree of the machine. The index translates into a single number the system global efficiency, by means of a particular combination of existing efficiency indicators. In its extended formulation, it can be applied, not only to AWGs, but also to other HVAC integrated systems, as well as to combinations of non-integrated and integrated solutions. In addition to equations, the paper provides calculation examples and a case study in order to show the practical application and advantages of GEI.

Influence Maximization with Latency Requirements on Social Networks

Targeted marketing strategies are of significant interest in the smartapp economy. Typically, one seeks to identify individuals to strategically target in a social network so that the network is influenced at a minimal cost. In many practical settings, the effects of direct influence predominate, leading to the positive influence dominating set with partial payments (PIDS-PP) problem that we discuss in this paper. The PIDS-PP problem is NP-complete because it generalizes the dominating set problem. We discuss several mixed integer programming formulations for the PIDS-PP problem. First, we describe two compact formulations on the payment space. We then develop a stronger compact extended formulation. We show that when the underlying graph is a tree, this compact extended formulation provides integral solutions for the node selection variables. In conjunction, we describe a polynomial-time dynamic programming algorithm for the PIDS-PP problem on trees. We project the compact extended formulation onto the payment space, providing an equivalently strong formulation that has exponentially many constraints. We present a polynomial time algorithm to solve the associated separation problem. Our computational experience on a test bed of 100 real-world graph instances (with up to approximately 465,000 nodes and 835,000 edges) demonstrates the efficacy of our strongest payment space formulation. It finds solutions that are on average 0.4% from optimality and solves 80 of the 100 instances to optimality. Summary of Contribution: The study of influence propagation is important in a number of applications including marketing, epidemiology, and healthcare. Typically, in these problems, one seeks to identify individuals to strategically target in a social network so that the entire network is influenced at a minimal cost. With the ease of tracking consumers in the smartapp economy, the scope and nature of these problems have become larger. Consequently, there is considerable interest across multiple research communities in computationally solving large-scale influence maximization problems, which thus represent significant opportunities for the development of operations research–based methods and analysis in this interface. This paper introduces the positive influence dominating set with partial payments (PIDS-PP) problem, an influence maximization problem where the effects of direct influence predominate, and it is possible to make partial payments to nodes that are not targeted. The paper focuses on model development to solve large-scale PIDS-PP problems. To this end, starting from an initial base optimization model, it uses several operations research model strengthening techniques to develop two equivalent models that have strong computational performance (and can be theoretically shown to be the best model for trees). Computational experiments on a test bed of 100 real-world graph instances (with up to approximately 465,000 nodes and 835,000 edges) attest to the efficacy of the best model, which finds solutions that are on average 0.4% from optimality and solves 80 of the 100 instances to optimality.

General Fractional Calculus: Multi-Kernel Approach

For the first time, a general fractional calculus of arbitrary order was proposed by Yuri Luchko in 2021. In Luchko works, the proposed approaches to formulate this calculus are based either on the power of one Sonin kernel or the convolution of one Sonin kernel with the kernels of the integer-order integrals. To apply general fractional calculus, it is useful to have a wider range of operators, for example, by using the Laplace convolution of different types of kernels. In this paper, an extended formulation of the general fractional calculus of arbitrary order is proposed. Extension is achieved by using different types (subsets) of pairs of operator kernels in definitions general fractional integrals and derivatives. For this, the definition of the Luchko pair of kernels is somewhat broadened, which leads to the symmetry of the definition of the Luchko pair. The proposed set of kernel pairs are subsets of the Luchko set of kernel pairs. The fundamental theorems for the proposed general fractional derivatives and integrals are proved.

Fatigue Assessment of Mooring Chain Considering the Effects Of Mean Load and Corrosion

Results from full scale fatigue tests of offshore mooring chains performed in recent years have revealed considerable influence of both mean load and corrosion condition on the fatigue capacity. It has been shown that a reduction of the mean load gives an increase in fatigue life, whereas the corrosion experienced by used chains have a significant negative impact. Neither of these effects are properly addressed by current S-N design curves or design practice. This paper suggests an extended S-N curve formulation, that includes the effects of mean load and corrosion condition. The parameters of the extended formulation are estimated empirically from mooring chain test data that includes new and used chains, with various mean loads and with different degrees of corrosion. The fitted capacity model is then used for fatigue calculation for the mooring system of a semi-submersible, showing the importance of using realistic mean loads and mooring chain corrosion in fatigue assessments.

The Running Intersection Relaxation of the Multilinear Polytope

The multilinear polytope of a hypergraph is the convex hull of a set of binary points satisfying a collection of multilinear equations. We introduce the running intersection inequalities, a new class of facet-defining inequalities for the multilinear polytope. Accordingly, we define a new polyhedral relaxation of the multilinear polytope, referred to as the running intersection relaxation, and identify conditions under which this relaxation is tight. Namely, we show that for kite-free beta-acyclic hypergraphs, a class that lies between gamma-acyclic and beta-acyclic hypergraphs, the running intersection relaxation coincides with the multilinear polytope and it admits a polynomial size extended formulation.

NB-IoT devices in reverberation chambers: a comprehensive uncertainty analysis

New protocols related to Internet-of-things applications may introduce previously unnoticed measurement effects in reverberation chambers (RCs) due to the narrowband nature of these protocols. Such technologies also require less loading to meet the coherence-bandwidth conditions, which may lead to higher variations, hence uncertainties, across the channel. In this work, we extend a previous study of uncertainty in NB-IoT and CAT-M1 device measurements in RCs by providing, for the first time, a comprehensive uncertainty analysis of the components related to the reference and DUT measurements. By use of a significance test, we show that certain components of uncertainty become more dominant for such narrowband protocols, and cannot be considered as negligible, as in current standardized test methods. We show that the uncertainty, if not accounted for by using the extended formulation, will be greatly overestimated and could lead to non-compliance to standards.

Popularity, Mixed Matchings, and Self-Duality

Our input instance is a bipartite graph G where each vertex has a preference list ranking its neighbors in a strict order of preference. A matching M is popular if there is no matching N such that the number of vertices that prefer N to M outnumber those that prefer M to N. Each edge is associated with a utility and we consider the problem of matching vertices in a popular and utility-optimal manner. It is known that it is NP-hard to compute a max-utility popular matching. So we consider mixed matchings: a mixed matching is a probability distribution or a lottery over matchings. Our main result is that the popular fractional matching polytope PG is half-integral and in the special case where a stable matching in G is a perfect matching, this polytope is integral. This implies that there is always a max-utility popular mixed matching which is the average of two integral matchings. So in order to implement a max-utility popular mixed matching in G, we need just a single random bit. We analyze the popular fractional matching polytope whose description may have exponentially many constraints via an extended formulation with a linear number of constraints. The linear program that gives rise to this formulation has an unusual property: self-duality. The self-duality of this LP plays a crucial role in our proof. Our result implies that a max-utility popular half-integral matching in G and also in the roommates problem (where the input graph need not be bipartite) can be computed in polynomial time.