Maximum Sum Research Articles

Morphological Variability of the Smelts (Osmeriformes: Osmeridae) of the Russian Far East

This paper presents the first study comparing the smallmouth smelts – the Japanese smelt Hypomesus nipponensis McAllister, 1963, the pond smelt H. olidus (Pallas, 1814), the marine smelt H. japonicus (Brevoort, 1856) – and the Asiatic smelt Osmerus dentex Steindachner et Kner, 1870 with the use of the variance of fluctuating asymmetry, the coefficient of variation, and the mean values of characters of these species. The comparison showed that the Asiatic smelt was characterized by the largest sum of dispersions of all characters, while the marine smelt had the smallest sum, which was obviously associated with more stable conditions of embryonic and early postembryonic development of the marine smelt. Japanese and pond smelts were similar in coefficients of variation for all traits. The Asiatic smelt displayed the maximum sum of coefficients of variation of all characters; while the marine smelt had the minimal sum of coefficients of variation of the characters, which may indicate relative morphological stability of this species in the range of its occurrence. A greater variability of smelts spawning in fresh water is in good agreement with the conclusion of G.V. Nikolsky et al. that the variability of traits in freshwater fish species is higher than in marine fish species. According to the average values for the characters, the four species of smelts differed only in the number of rays in the pectoral fins, while the minimum value was typical of the pond smelt, and the maximum value – for the marine smelt. The Japanese (24) and pond (26) smelts showed the minimum differences from other species, and the marine and Asiatic smelts – maximum differences (28).

10 important financial investments for orthopods in India

10 important financial investments for orthopods in India

Solving the p-second center problem with variable neighborhood search

The p-center problem is a well-known and highly studied problem pertaining to the identification of p of the potential n center locations in such a way as to minimize the maximum distance between the users and the closest center. As opposed to the p-center, the p-second center problem minimizes the maximum sum of the distances from the users to the closest and the second closest centers. In this paper, we propose a new Variable Neighborhood Search based algorithm for solving the p-second center problem. Its performance is assessed on the benchmark instances from the literature. Moreover, to further evaluate the algorithm?s performance, we generated larger instances with 1000, 1500, 2000, and 2500 nodes and instances defined over graphs up to 1000 nodes with different densities. The obtained results clearly demonstrate the effectiveness and efficiency of the proposed algorithm.

Throughput Analysis of HARQ Scheme Based on Full-Duplex Two-Way AF SWIPT Relay

The simultaneous wireless information and power transfer (SWIPT) relay system is one of the emerging technologies. Xiaomi Corporation and Motorola Inc. recently launched indoor wireless power transfer equipment is one of the most promising applications. To tap the potential of the system, hybrid automatic repeat request (HARQ) is introduced into the SWIPT relay system. Firstly, the time slot structure of HARQ scheme based on full duplex two-way amplify and forward (AF) SWIPT relay is given, and its retransmission status is analyzed. Secondly, the equivalent signal-to-noise ratio and outage probability of various states are calculated by approximate simplification. Thirdly, the energy harvesting power in each state is calculated. Finally, the energy harvested-throughput sum function is constructed to characterize the performance of energy harvesting and data transmission. Simulation results show that the proposed HARQ scheme has better energy harvested-throughput sum function than the traditional HARQ scheme. When P2 = 22 dB, the maximum sum function is 54.86% (the proposed HARQ scheme) and 52.307% (the traditional HARQ scheme), respectively.

The maximum sum of the sizes of cross $ t $-intersecting separated families

<abstract><p>For a set $ X $ and an integer $ r\geq 0 $, let $ {X \choose \leq r} $ denote the family of subsets of $ X $ that have at most $ r $ elements. Two families $ \mathcal{A}\subset {X\choose \leq r} $ and $ \mathcal{B}\subset {X\choose \leq s} $ are cross $ t $-intersecting if $ |A\cap B|\geq t $ for all $ A\in\mathcal{A}, B\in\mathcal{B} $. In this paper, we considered the measures of cross $ t $-intersecting families $ \mathcal{A}\subset {X\choose \leq r} $, $ \mathcal{B}\subset {X\choose \leq s} $, then we used this result to obtain the maximum sum of sizes of cross $ t $-intersecting separated families.</p></abstract>

Brooks' theorem for 2-fold coloring

The two-fold chromatic number of a graph is the minimum number of colors needed to ensure that there is a way to color the graph so that each vertex gets two distinct colors, and adjacent vertices have no colors in common. The Ore degree is the maximum sum of degrees of an edge in a graph. We prove that, for 2-connected graphs, the two-fold chromatic number is at most the Ore degree, unless G is a complete graph or an odd cycle.

Asymptotic pressure on some self-similar trees

The vertices of the Cayley graph of a finitely generated semigroup form a set of sites which can be labeled by elements of a finite alphabet in a manner governed by a nonnegative real interaction matrix, respecting nearest neighbor adjacency restrictions. To the set of these configurations one can associate a pressure, which is defined as the limit, when it exists, of averages of the logarithm of the partition function over certain finite subgraphs. We prove that for shifts of finite type on generalized Fibonacci trees and many primitive interaction matrices, the limit exists and is given by an infinite series. We also show that the limit of any cluster points of the pressure on finite subtrees as the number of generators grows without bound, which we call the asymptotic pressure, equals the logarithm of the maximum row sum of the interaction matrix.

A Complete Characterization of Bipartite Graphs with Given Diameter in Terms of the Inverse Sum Indeg Index

In 2010, Vukičević introduced an new graph invariant, the inverse sum indeg index of a graph, which has been studied due to its wide range of applications. Let Bnd be the class of bipartite graphs of order n and diameter d. In this paper, we mainly characterize the bipartite graphs in Bnd with the maximal inverse sum indeg index. Bipartite graphs with the largest, second-largest, and smallest inverse sum indeg indexes are also completely characterized.

Пошук максимальних незалежних множин вершин графа для вдосконалення програмних проєктів

The need is fixed to software project enhancing with seamless integration of technological-descriptive and normative project manage- ment approaches by means of classical Graph Discrete Optimization Problems tailoring for software project management tasks, poorly equipped with best practices within technological approach. Class of software project management tasks is proposed to demonstrate the benefits of such integration. Two Boolean linear programming problems are investigated for searching some maximum size indepen- dent set (Section 1) and an algorithm for searching all possible maximum size independent sets (Section 2). Section 3 presents Problem Statement for searching a given number of non-intersecting independent sets with maximum sum of vertices’ numbers within independent sets. Based on it, Vizing-Plesnevich algorithm is described for coloring the graph vertices with the minimum number of colors. To solve Boolean problems, both specialized mathematical programming language AMPL and corresponding solver program named gu- robi are used. For basic algorithms developed, reference AMPL code versions are given as well as their running results. Illustrative examples of software project enhancing with the algorithms elaborated are considered in Section 4, namely: 25 specialists being conflicted during their previous projects partitioning into coherent conflict-free sub-teams for software projects portfolio; schedule optimization for autonomous testing of reusable components within a critical software system; cores composing for independent teams in a critical software project.

Energy-efficient resource allocation for NOMA heterogeneous networks using feedback water cycle algorithm

In recent years, nonorthogonal multiple access (NOMA) has grasped the attention of all researchers in both industrial and academic fields because it has been regarded as an effective solution for 5G technologies to maximize spectral efficiency and connectivity of the system. Also, it has sufficient potential to maximize the performance of a network. Besides, the deployment of NOMA in heterogeneous networks (HetNets) satisfies the requirements of user’s explosive data traffic. However, the increasing demand for energy consumption of the wireless network provokes the researchers to establish an energy-efficient resource allocation scheme. The applications of NOMA provide better utilization of spectrum efficiency and minimize the cost of resource allocation. The resource allocation problem in wireless networks still remains a challenging task as the HetNets are suffered from mutual cross-tier interference. Hence, this research proposes a new effective hybrid optimization-based energy-efficient resource allocation scheme for NOMA HetNets by introducing a newly proposed method called Feedback Water Cycle Algorithm (FWCA). The method evaluates the user-pairing and sub-channel issue for reducing computational complexity. In addition to this, the network is analyzed for determining the power consumption and energy model with dynamic coefficients. Moreover, the developed FWCO obtained the maximum achievable rate of 25.992[Formula: see text]Mbps/Hz, maximum energy efficiency of 77.398%, maximum sum rate of 31.748[Formula: see text]Mbps/Hz, and maximum throughput of 8.888[Formula: see text]Mbps.

User Pairing and Power Allocation for IRS-Assisted NOMA Systems With Imperfect Phase Compensation

In this letter, we analyze the performance of the intelligent reflecting surface (IRS) assisted downlink non-orthogonal multiple access (NOMA) systems in the presence of imperfect phase compensation. We derive an upper bound on the imperfect phase compensation to achieve minimum required data rate for each user. Using this bound, we propose an adaptive user pairing algorithm to maximize the network throughput. We then derive bounds on the power allocation factors and propose power allocation algorithms for the paired users to achieve the maximum sum rate or ensure fairness. Through extensive simulations, we show that the proposed algorithms significantly outperform the state-of-the-art algorithms in the presence of phase imperfections.

The Hsu–Robbins–Erdös theorem for the maximum partial sums of quadruplewise independent random variables

Etemadi (1981) [10] and Rio (1995) [27] provided proofs of the Kolmogorov–Marcinkiewicz–Zygmund strong law of large numbers under optimal moment conditions without using the Kolmogorov-type maximal inequalities. While this famous result holds for sequences of pairwise independent identically distributed real-valued random variables, a closely related result, the Hsu–Robbins–Erdös strong law of large numbers may fail if the underlying random variables are only assumed to be pairwise independent identically distributed. This note develops Rio's method and uses an approximation technique to establish the Hsu–Robbins–Erdös strong law of large numbers for the maximum partial sums of quadruplewise independent identically distributed random variables. We consider random variables taking values in a real separable Banach space X, but the main result is new even when X is the real line. Previous contributions so far considered the complete convergence of the partial sums or restricted to dependence structures satisfying a Kolmogorov-type maximal inequality.

Grey neural network channel estimation and RBFNN hybrid precoding schemes for the multi user millimeter wave massive MIMO

AbstractThe millimeter wave (mm‐wave) multi‐input multi‐output (MIMO) communications are the most promising technology specially developed for next‐generation wireless networks so that the throughput and available spectrum of the network has been massively increased. At base station, it has a large number of antenna arrays with coherent transceiver processing, which helps to increase spectral efficiency. Each antenna in conventional MIMO systems makes use of a single radio‐frequency (RF) chain to boost multiplexing gain. Additionally, due to broader bandwidth, channel frequency is selective and signal‐to‐noise (SNR) is low. A successful channel estimation training phase is thus required. However, the utilization of a huge number of antennas leads to unaffordable hardware costs and excessive power usage. In order to deliver high array gain at a more affordable price, hybrid precoding techniques are applied. Both baseband combinational matrix and baseband precoding matrix must be optimised when transmitter and receiver sides of mm‐wave MIMO systems adopt hybrid precoding architecture. In addition, the combinational matrix and the precoding matrix have to be simulated to obtain the maximum system sum rate. This requires an efficient hybrid precoding approach for generating improved array gain. Therefore, this work uses a novel grey neural network approach for channel estimation and radial basis function neural network (RBFNN) for hybrid precoding. For effective channel estimation, grey wolf optimization (GWO) works in conjunction with artificial neural networks (ANN) to produce optimum results. In mm‐wave MIMO systems, the hybrid precoding RBFNN offers reduced complexity and increased efficiency. As a result, the proposed work adopts neural networks to provide effective channel estimation and hybrid precoding.

Fault tolerance analysis for hamming graphs with large-scale faulty links based on k-component edge-connectivity

The L-ary n-dimensional hamming graph KLn is one of the most attractive interconnection networks for parallel processing and computing systems. Analysis of the link fault tolerance of topology structure can provide the theoretical basis for the design and optimization of the interconnection networks. The k-component edge-connectivity cλk(G) of an interconnection network G, is the minimum number of set of faulty links, such that these malfunctions disconnect the network G with at least k connected subnetworks. It gives a more precise quantitative analysis of indicators of the robustness of a parallel distributed system in the event of faulty links. Let t=⌊n2⌋ if L is even, and t=⌈n2⌉ if L is odd. In this paper, we prove that the (k+1)-component edge-connectivity of L-ary n-dimensional hamming graphs is cλk+1(KLn)=(L−1)nk−exk(KLn)2 for k≤Lt, n≥7, where exk(KLn) represents the maximum degree sum of the subgraph induced by all k processors of KLn. As the exact values of (k+1)-component edge-connectivity of KLn oscillate greatly, an efficient O(log⁡N) algorithm is designed to determine the exact values of cλk+1(KLn) for each k≤Lt and N=Ln. Our result improves those of Xu et al. [33] and Liu et al. [27].

Vertex neighborhood restricted edge achromatic sums of graphs

The vertex induced 2-edge coloring number [Formula: see text] of a graph [Formula: see text] is the highest number of colors that can occur in an edge coloring of a graph [Formula: see text] such that not more than two colors can be used to color the edges in the induced subgraph [Formula: see text] generated by the closed neighborhood [Formula: see text] of a vertex [Formula: see text] in [Formula: see text]. The vertex induced 2-edge coloring sum of a graph [Formula: see text] denoted as [Formula: see text], is the greatest sum among all the vertex induced 2-edge coloring of a graph [Formula: see text] which concedes [Formula: see text] colors. The vertex incident 2-edge coloring number of a graph [Formula: see text] is the highest number of colors required to color the edges of a graph [Formula: see text] such that not more than two colors can be ceded to the edges incident at the vertex [Formula: see text] of [Formula: see text]. The vertex incident 2-edge coloring sum of a graph [Formula: see text] denoted as [Formula: see text], is the maximum sum among all the vertex incident 2-edge coloring of graph [Formula: see text] which receives maximum [Formula: see text] colors. In this paper, we initiate a study on the vertex induced 2-edge coloring sum and vertex incident 2-edge coloring sum concepts and apply the same to some graph classes. Besides finding the exact values of these parameters, we also obtain some bounds and a few comparative results.

Exploring Sum Rate Maximization in UAV-Based Multi-IRS Networks: IRS Association, UAV Altitude, and Phase Shift Design

This paper studies the unmanned aerial vehicle (UAV) based multiple intelligent reflecting surface (IRS) network, where the hovering UAV acts as a base station, and the IRS enhances signal transmission to across obstacle between users and UAV. To achieve the maximum sum rate of proposed communication scenario, a non-convex problem considering IRS association results, hovering altitude of UAV, and the phase shift design of multi-IRS is formulated. From the IRS association problem, we can find that the IRS association results are coupled to the decoding order of non-orthogonal multiple access (NOMA). To tackle this, a mathematical interference expansion scheme is developed to decouple it and transform it to convex by binary relaxation method. The non-convexity of hovering altitude optimization problem is solved by logarithm operation, approximation, and auxiliary matrices. For the phase shift optimization problem of multi-IRS, we propose a gradient approximation based initial scheme and develop a univariate optimization based approach on the basis to achieve the users sum rate improvement in multi-IRS. In the end, we compare the proposed scheme with baseline scheme to present the superiority of this work under various network settings. The internal reasons for the variation of simulation results are also analyzed.

Load-Aware Distributed Resource Allocation for MF-TDMA Ad Hoc Networks: A Multi-Agent DRL Approach

Without control center assistance, it is difficult that users take traffic loads of whole Ad Hoc networks into account to utilize wireless resources collaboratively. Considering influence of load differences between users on resource allocation can be learned in advance, we construct a framework of load-aware distributed resource allocation for multiple frequencies time division multiple access (MF-TDMA) wireless Ad Hoc networks based on multi-agent deep reinforcement learning (DRL) with centralized training and distributed execution. In this framework, each user is regarded as an agent and the wireless transmission resources are partitioned into time-frequency resource blocks (RBs). Each user reserves RBs by sending network manager operational packet (NMOP) in turn at rotating broadcast stage (RBS) and how many RBs each user reserves depends on the corresponding agent's decision. The main innovative point of our work is achieving a result of wireless resource allocation that balance load degree of all users on the whole network in a distributed manner. With defining a novel network utility parameterized by traffic loads (termed timely capacity), we first model the resource allocation as an optimization problem for timely capacity sum maximization. Using the optimization objective as common reward function to train neural networks of all agents in an offline simulation environment, we obtain the distributed algorithm based on multi-agent DRL. Experimental results demonstrate that with the neural networks trained by the designed reward and enough training, users can successfully learn to collaboratively improve network utility in distributed implementation.

Causal relationships between birth weight, childhood obesity and age at menarche: A two-sample Mendelian randomization analysis.

Observational studies suggest birth weight and childhood obesity are closely associated with age at menarche. However, the relationships between them are currently inconsistent and it remains elusive whether such associations are causal. Therefore, the aim of the study was to investigate whether there existed causal relationships between birth weight, childhood obesity and age at menarche. A two-sample Mendelian randomization (MR) study. The standard inverse variance weighted MR analyses were adopted to evaluate the causal effects of birth weight (n = 143,677), childhood body mass index (BMI) (n = 39,620) on age at menarche (n = 182,416) with summary statistics from large-scale genome-wide association studies(GWASs). Meanwhile, we validated our MR results with some sensitivity analyses including maximum likelihood, weighted-median and MR pleiotropy residual sum and outliermethods. The present study showed that each one standard deviation (1-SD) lower birth weight was predicted to result in a 0.1479 years earlier of age at menarche (β = .1479, 95% confidence interval [CI] = 0.0422-0.2535; p = 0.0061). We also found that genetically predicted 1-SD increase in childhood BMI was causally associated with early age at menarche (β = -.3966, 95%CI = -0.5294 to -0.2639; p = 4.73E-09). Our MR study suggests the causal effect of lower birth weight and higher childhood BMI on the increased risk of earlier menarche. It may be the opportune time to carry out weight control intervention in prenatal and early childhood development periods to prevent early menarche onset, thus decreasing the future adverse consequences.

Dynamically second-preferred [formula omitted]-center problem

This paper deals with the Dynamically Second-preferred p-center Problem (DSpP). In this problem, customers’ preferences and subsets of sites that each customer is willing to accept as service centers are taken into account. It is assumed that centers can fail and, thus, the decision maker is risk-averse and makes his decision taking into account not only the most favourite centers of the customers but also the worst case situation whenever they evaluate their preferred second opportunity. Specifically, the new problem aims at choosing at most p centers so that each demand point can visit at least two acceptable centers and the maximum sum of distances from any demand point to any of its preferred centers plus the distance from any of the preferred centers to any of the centers the user prefers once he is there is minimized. The problem is NP-hard as an extension of the p-next center problem. The paper presents three different mixed-integer linear programming formulations that are valid for the problem. Each formulation uses different space of variables giving rise to some strengthening using valid inequalities and variable fixing criteria that can be applied when valid upper bounds are available. Exact methods are limited so that a heuristic algorithm is also developed to provide good quality solution for large size instances. Finally, an extensive computational experience has been performed to assess the usefulness of the formulations to solve DSpP using standard MIP solvers.

A Multi-Indicator Evaluation Method for Spatial Distribution of Urban Emergency Shelters

Evaluation of the spatial distribution of urban emergency shelters can effectively identify defects in the current distribution of urban emergency shelters and weaknesses in the overall evacuation service capacity of the city and provide reference for improving the level of urban emergency shelters and evacuation and disaster relief capacity. At present, evaluation of the spatial distribution of urban emergency shelters is mainly carried out on three aspects: effectiveness, accessibility, and safety. However, there are problems, such as individual evaluation scales and incomplete indicator systems, unreasonable allocation of indicator weights, and ignoring the influence of fuzzy incompatibility between different indicator attributes on the evaluation results. In this paper, we start from two scales, the individual emergency shelter and the regional groups of emergency shelters. Based on the five criteria of effectiveness, accessibility, safety, suitability, and fairness, the evaluation indicator system of the spatial distribution of urban emergency shelters was constructed. It was combined with AHP, CRITIC, the optimal weight coefficient solution method based on the maximum deviation sum of squares theory, and fuzzy optimization theory to construct a multi-indicator evaluation model. Further, the spatial distribution condition of the existing emergency shelter in Shanghai was evaluated. The results show that: among the existing ninety-one emergency shelters in Shanghai, there are nine places with unreasonable spatial distribution; nineteen places are comparatively unreasonable. From the scale of regional groups, there is one district (Pudong New District) with unreasonable spatial distribution: its relative superiority value is far lower than other districts, and there are three districts that are comparatively unreasonable. Further, the evaluation scores of the spatial distribution reasonableness of emergency shelters in each region of Shanghai show a high–low–middle distribution from the downtown area of Shanghai outward. The evaluation indicator system and evaluation method used in this paper can effectively reflect the deficiencies in the spatial distribution of urban emergency shelters, thus providing a reference for the relevant departments to improve and plan emergency shelters.