Let \( G = (V, E) \) be a graph with minimum degree at least one. The general inverse degree of \( G \) is defined as \(\sum\limits_{v \in V} \frac{1}{d^{\alpha}(v)}\), where \( \alpha \) is a real number with \( \alpha > 0 \). In this paper, we present sufficient conditions involving the general inverse degree with \( \alpha \geq 1 \) for some Hamiltonian properties of graphs and upper bounds for the general inverse degree with \( \alpha \geq 1 \).

In today’s era, the rapid development of artificial intelligence is transforming warehousing and logistics by enhancing efficiency and reducing labor costs. In this paper, we first employ a least squares support vector machine to develop an inventory prediction model for warehousing logistics, accurately forecasting inventory values. Next, we design an automated logistics and warehousing architecture that facilitates seamless data transfer and information feedback. Finally, this architecture is used to build a comprehensive inventory management model. Our analysis shows that the AI-based prediction nearly matches the actual inventory value (229 vs. 230) and achieves an inventory turnover rate of 5 times per month, which significantly reduces backlog and improves overall management efficiency and user satisfaction.

The Cascaded Integrator Comb (CIC) decimation filter is a pivotal technology extensively employed in digital signal processing (DSP). This paper delves into a comprehensive examination of the CIC algorithm within software-defined radio (SDR) systems from the perspective of parallel computing and introduces a novel Non-Recursive Implementation (NR-I) on an NVIDIA GPU using CUDA. The NR-I approach significantly reduces computational load by unfolding the recursive CIC structure with pre-derived Unfold Factors. Further optimization was achieved through data-transfer enhancements using PM Implementation (PM-I) and ODT Implementation (ODT-I). Experimental results demonstrate that NR-I achieves a speedup of over 449.48. Additionally, the data-transfer optimizations resulted in substantial performance improvements, with PM-I and ODT-I reducing execution time by 43.24% and 64.22%, respectively. The GPU implementation’s speedup is significantly greater than that of OpenMP, ranging from 3.34 to 10.22 times. These results underscore the effectiveness of the proposed Non-Recursive Implementation in accelerating time-intensive and data-intensive computations.

This paper presents a new sequence called the \(k-\)division sequence. The Pell and Lehmer sequences are then used to define new sequences called the \(k-\)division \(L-\)Lehmer-Pell sequences and some properties of these sequences are determined. Then the \(k-\)division \(L-\)Lehmer-Pell sequences and corresponding self-invertible matrices are used in a new Affine-Hill cipher algorithm. The security of this cipher is examined.

In the era of globalization and intense market competition, strategic human resource management (SHRM) is critical for boosting corporate competitiveness. This study employs structural equation modeling (SEM) and multiple linear regression to uncover the complex influence of SHRM perceptions on employee proactive behaviors, and uses a convolutional neural network (CNN) to explore nonlinear relationships and validate the SEM findings. Results reveal that SHRM perception has a significant positive effect on employee proactive behavior (\(\beta = 0.254\), \(p<0.001\)). Mediators such as job self-efficacy and conceptual psychological contract play a positive role, with indirect effects of 0.1043 and 0.1726, respectively, while insider identity perception significantly moderates the relationship (\(\beta = 0.09\), \(p<0.01\)). The CNN model ranks the importance of variables in descending order as: conceptual psychological contract, job self-efficacy, SHRM perception, job category, and insider identity perception, consistent with the SEM results. These findings highlight the potential of CNNs to optimize HR strategies and enhance employee motivation.

One of the urgent challenges in auditing today is preventing accounting management risk. This study integrates big data auditing technology to enhance audit quality by developing an audit risk assessment index system based on material misstatement risk and inspection risk. By combining the hierarchical analysis and entropy weighting methods to assign risk indicators, the accounting audit risk index for Company Z was calculated using a multi-level fuzzy comprehensive evaluation method and regression analysis to examine impact factors. Empirical evidence shows that the overall expected audit risk is 0.412—indicating a low to average risk level—with significant correlations between the previous year’s audit opinion, audit fee, and other factors such as the largest shareholder’s holding, board size, percentage of independent directors, operating income growth, net profit, and the audit environment. The study focuses on developing effective prevention and response strategies in the era of big data and offers recommendations to reduce potential auditing risks.

A radio labeling of a graph \( G \) is a mapping \( f : V(G) \to \{0, 1, 2, \dots\} \) such that \( |f(u)-f(v)| \geq \text{diam}(G) + 1 – d(u,v) \) for every pair of distinct vertices \( u,v \) of \( G \), where \( \text{diam}(G) \) is the diameter of \( G \) and \( d(u,v) \) is the distance between \( u \) and \( v \) in \( G \). The radio number \( \text{rn}(G) \) of \( G \) is the smallest integer \( k \) such that \( G \) admits a radio labeling \( f \) with \( \max\{f(v) : v \in V(G)\} = k \). In this paper, we give a lower bound for the radio number of the Cartesian product of a tree and a complete graph and give two necessary and sufficient conditions for the sharpness of the lower bound. We also give three sufficient conditions for the sharpness of the lower bound. We determine the radio number of the Cartesian product of a level-wise regular tree and a complete graph which attains the lower bound. The radio number of the Cartesian product of a path and a complete graph derived in [B. M. Kim, W. Hwang, and B. C. Song, Radio number for the product of a path and a complete graph, J. Comb. Optim., 30 (2015), 139–149] can be obtained using our results in a short way.

Let \( G \) be a connected graph with \( m \) edges. The density of a nontrivial subgraph \( H \) with \( \omega(H) \) components is \( d(H) = \frac{|E(H)|}{|V(H)| – \omega(H)} \). A graph \( G \) is uniformly dense if for any nontrivial subgraph \( H \) of \( G \), \( d(H) \leq d(G) \). For each cyclic ordering \( o=(e_1, e_2, \dots, e_m) \) of \( E(G) \), let \( h(o) \) be the largest integer \( k \) such that every \( k \) cyclically consecutive elements in \( o \) induce a forest in \( G \); and the largest \( h(o) \), taken among all cyclic orderings of \( G \), is denoted by \( h(G) \). A cyclic ordering \( o \) of \( G \) is a cyclic base ordering if \( h(o) = |V(G)| – \omega(G) \). In [15], Kajitani et al. proved that every connected nontrivial graph with a cyclic base ordering is uniformly dense, and conjectured that every uniformly dense graph has a cyclic base ordering. This motivates the study of \( h(G) \). In this paper, we investigate the value of \( h \) for some families of graphs and determine all connected graphs \( G \) with \( h(G) \leq 2 \).

An open-locating-dominating set of a graph models a detection system for a facility with a possible “intruder” or a multiprocessor network with a possible malfunctioning processor. A “sensor” or “detector” is assumed to be installed at a subset of vertices where each can detect an intruder or a malfunctioning processor in its neighborhood, but not at its own location. We consider a fault-tolerant variant of an open-locating-dominating set called an error-correcting open-locating-dominating set, which can correct a false-positive or a false-negative signal from a detector. In particular, we prove the problem of finding a minimum error-correcting open-locating-dominating set in an arbitrary graph is NP-complete. Additionally, we characterize the existence criteria for an error-correcting open-locating-dominating set in an arbitrary graph. We also consider extremal graphs that require every vertex to be a detector and minimum error-correcting open-locating-dominating sets in infinite grids.

Let \( G = (V, E) \) be a graph with vertex set \( V \) and edge set \( E \). A set \( S \subset V \) is a dominating set if every vertex in \( V – S \) is adjacent to at least one vertex in \( S \), an independent set if no two vertices in \( S \) are adjacent, and a total dominating set if every vertex in \( V \) is adjacent to at least one vertex in \( S \). The domatic number \( \text{dom}(G) \), idomatic number \( \text{idom}(G) \), and total domatic number \( \text{tdom}(G) \), of a graph \( G \) equal the maximum order \( k \) of a partition \( \pi = \{V_1, V_2, \ldots, V_k\} \) of \( V \) into {dominating sets, independent dominating sets, total dominating sets}, respectively. A queens graph \( Q_n \) is a graph defined on the \( n^2 \) squares of an \( n \)-by-\( n \) chessboard, such that two squares are adjacent if and only if a queen on one square can move to the other square in one move, that is, the two squares lie on a common row, column, or diagonal. In this note, we determine the value of these three numbers for \( Q_n \) for the first several values of \( n \). In addition, we introduce the concepts of graphs being \( \gamma \)-domatic, \( i \)-domatic, \( \alpha \)-domatic, \( \Gamma \)-domatic, \( \gamma_t \)-domatic, and \( \Gamma_t \)-domatic.