The audio-integrated active noise control (AIANC) system is a special type of active noise control (ANC) system that aims to suppress noise while broadcasting audio. Although the nonlinear effect in ANC systems has been studied for many years, current research on AIANC systems still focuses on linear approaches, which cannot match the practical systems well and will lead to performance degradation. This paper proposes a new nonlinear AIANC method based on the psychoacoustic gated convolutional recurrent network (PGCRN). First, a new AIANC system model is developed based on the gated convolutional recurrent network (GCRN). Then a psychoacoustic model is introduced to the loss function of the GCRN to improve the audio quality. Finally, a new automatic gain control (AGC) method based on the MFCC cosine similarity and the XE-NLMS algorithm is proposed for the new AIANC system to improve audio quality under low signal-to-noise rate (SNR) conditions. Experimental results show that the proposed AIANC method outperforms several conventional methods in different noisy and nonlinear environments.

Forward security is a fundamental requirement in searchable encryption, where a newly generated ciphertext is not allowed to be searched by previously generated trapdoors. However, forward security is somewhat overlooked in the public key encryption with keyword search (PEKS) context and there are few proposals, whereas forward security has been stated as a default security notion in the (dynamic) symmetric searchable encryption (SSE) context. In this paper, we propose a generic construction of forward secure public key authenticated encryption with keyword search (FS-PAEKS) from PAEKS. In addition to PAEKS, we employ 0/1 encodings proposed by Lin et al. (ACNS 2005). We also show that the Jiang et al.'s FS-PAEKS scheme (The Computer Journal 2023) does not provide forward security. Our generic construction is quite simple, and it can also be applied to construct forward secure public key encryption with keyword search (FS-PEKS). Our generic construction yields a comparably efficient FS-PEKS scheme compared to the previous scheme. Moreover, it eliminates the hierarchical structure (Abdalla et al. (JoC 2016)) or attribute-based feature (Zeng et al. (IEEE Transactions on Cloud Computing 2022)) of the previous generic constructions which is meaningful from a feasibility perspective.

An effective method for virtualized network function forwarding graph (VNF-FG) placing based on graph attention network (GAT) and reinforcement learning (RL) is proposed for complex services and dynamic network conditions. We formulate a VNF-FG placing optimization problem, and designed a GAT-based RL agent to recognize graph structure and obtain placing policy. Experiments prove the method effectiveness.

APN functions provide the optimal resistance to differential attacks. In 2022, Li et al. [IEEE TIT 68(7), 4761-4769 (2022)] constructed an infinite family of quadratic APN functions over $\mathbb{F}_{2^{2m}}$ with $\gcd(3,m)=1$ in the bivariate form $F(x,y)=(x^{3}+xy^{2}+y^{3}+xy,x^{5}+x^{4}y+y^{5}+xy+x^{2}y^{2})$. In this work, we theoretically prove that functions in a more general form $F'(x,y)=(x^{2^k+1}+xy^{2^k}+y^{2^k+1}+\sum_{i=0}^{k-1}(xy)^{2^i}, x^{2^{2k}+1}+x^{2^{2k}}y+y^{2^{2k}+1}+\sum_{i=0}^{k-1}(xy+(xy)^{2^k})^{2^i})$ are CCZ-inequivalent to APN power functions on $\mathbb{F}_{2^{2m}}$ with $\gcd(3k,m)=1$.

The integration of numerous IoT devices into the distribution network supports coordinated control of grid-connected devices, but the complex topology of distribution networks and uneven base station distribution result in weak coverage and uneven load, leading to poor end-to-end latency performance. While IoT heterogeneous integrated networking technologies enable low-latency access for many power devices, challenges like communication resource competition and slow optimization under uncertain network conditions remain. To address these issues, this paper proposes a joint optimization model for relay scheduling, data compression, and time scheduling, aiming to minimize average end-to-end latency. A two-stage edge-end cooperative resource optimization algorithm based on Lyapunov optimization theory is proposed. In the first stage, a relay scheduling algorithm using relay device connectivity and queue delay-aware ascending price matching optimizes scheduling by dynamically adjusting channel matching costs based on connectivity and queue backlogs. The second stage introduces a delay deviation-aware adaptive particle swarm optimization to optimize time scheduling and data compression, achieving fast convergence. The relay scheduling preferences are updated based on the final objective function value. Simulation results demonstrate the method's effectiveness in reducing latency, improving network performance, and efficiently utilizing network resources.

We propose a zero-order-hold (ZOH) triggered prescribed-time controller for a chain of integrators. Our proposed controller derives the state into the arbitrarily small ball around the origin at the prescribed-time irrespective of the initial conditions while the control input is only updated discretely. We carry out the rigorous system analysis using Razumikhin theorem to prove the boundness of the state and control input. We give simulation results to illustrate the validity of our control method.

Global routing is one of the most crucial steps for design closure in the physical design of VLSI. This paper proposes a routing algorithm, called UEO algorithm, for generalized channels to achieve a small local congestion which is mainly dedicated to global routing for CMOS circuits designed to match 3D bonding technology. In our generalized channel formulation, due to tight global horizontal routing capacity, the connection of a net is restricted to a single-trunk Steiner tree. Routing algorithms proposed for the generalized channel so far achieve a small total vertical wire length while achieving the minimum number of used tracks, but they do not take a local vertical congestion into account, and the completion of detailed routing may suffer from a large local vertical congestion. The proposed UEO algorithm iteratively determines the assignment of trunks of nets based on the net priority proposed in this paper to achieve a small local vertical congestion. In experiments, it is confirmed that UEO achieves a small local vertical congestion, and that this work contributes to achieve design closure of routing design for 3D VLSI.

Multi-attribute decision-making (MADM) is crucial in various fields. Most of MADM methods based on attribute values primarily handle scenarios where attribute information is expressed as an exact value. With the wide application of methods, the problem of uncertainty arises gradually, leading to attribute values that are not single values. The paper constructs a three-way decision (TWD) model based on probabilistic dominance relation (PDR) under interval-valued intuitionistic fuzzy number (IVIFN). This model is designed to address imprecise information by utilizing IVIFN. Meanwhile, we innovatively introduce attribute dominance degree to construct loss function matrix, which makes full use of interval number information. Moreover, we propose a novel method to calculate conditional probability under PDR, thus constructing a novel TWD model that assists decision makers in ranking and classifying. Finally, this paper demonstrates the reliability of the model in ranking through Spearman rank correlation coefficient (SRCC). Furthermore, the experimental result on UCI dataset shows that the model has great classification capabilities, with a 3.1% reduction in the average error rate.

Differential privacy is used to guarantee privacy protection and has become the de facto standard for privacy protection data analysis. The (α, ε) -Rényi differential privacy ((α, ε) -RDP), which is based on the Rényi divergence, has been proposed as a relaxation of the ε-differential privacy (ε-DP). The Rényi divergence is a generalization of the Kullback-Leibler divergence. The f-divergence, on the other hand, is also a generalization of the Kullback-Leibler divergence, where f: [0, ∞) → ℝ is a convex function satisfying f (1) = 0. Hence, we can consider differential privacy based on the f-divergence in the same manner as the Rényi differential privacy. This paper introduces (f, ε) -differential privacy ((f, ε) -DP) based on the f-divergence. We prove a novel composition theorem of an adaptive composition of n mechanisms all satisfying ε-DP. To derive this result, the following three propositions play an important role: (i) a probability preservation inequality via the f-divergence; (ii) a composition of two (f, ε) -DP; (iii) a relationship between the ε-DP and the (f, ε) -DP. Numerical examples show that there are cases where the proposed composition theorem is tighter than the previous composition theorems.

A Hopfield network is a mathematical model of a spin glass system, a theory of stochastic physics. This binary model has been extended to many high-dimensional models. A persistent challenge in these models has been determining the activation function and stability conditions. In this paper, we propose an algebraic Hopfield network (AHN), which encompasses most extensions of classic Hopfield networks. In AHNs, weights act as operators on neuron outputs in weighted sum inputs. Here we provide the activation function and stability conditions for AHNs, offering a foundation for developing novel Hopfield network models.

We investigate the computational complexity of a simple one-dimensional origami problem. We are given a paper strip P of length n + 1 and fold it into unit length by creasing at unit intervals. Consequently, we have several paper layers at each crease in general. The number of paper layers at each crease is called the crease width at the crease. For a given mountain-valley assignment of P, in general, there are exponentially many ways of folding the paper into unit length consistent with the assignment. It is known that the problem of finding a way of folding P to minimize the maximum crease width of the folded state is NP-complete. In this study, we investigate a related paper-folding problem. For any given folded state of P, each crease has its mountain-valley assignment and crease-width assignment. Then, can we retrieve the folded state uniquely when only partial information about these assignments is given? We introduce this natural problem as the crease-retrieve problem, for which there are a number of variants depending on the information given about the assignments. In this paper, we show that some cases are polynomial-time solvable and that some cases are strongly NP-complete.

In this paper we first define (t, s)-completely independent spanning trees, which is a generalization of completely independent spanning trees. A set of t spanning trees of a graph is (t, s)-completely independent if, for any pair of vertices u and v, among the set of t paths from u to v in the t spanning trees, at least s ≤ t paths are internally disjoint. By (t, s)-completely independent spanning trees, one can ensure any pair of vertices can communicate each other even if at most s - 1 vertices break down. We prove that every maximal planar graph has a set of (3, 2)-completely independent spanning trees, every tri-connected planar graph has a set of (3, 2)-completely independent spanning trees, and every 3D grid graph has a set of (3, 2)-completely independent spanning trees. Also one can compute them in linear time.

The stream version of asymmetric binary systems (ABS) invented by Duda is an entropy coder for information sources with a finite alphabet. It has the state parameter l of a nonnegative integer and the probability parameter p with 0 < p < 1. Firstwe observe that the edge shift X_G associated with the stream version of ABS has the topological entropy h(X_G) = log 2. Then we define the edge shift X_H associated with output blocks from the stream version of ABS, and show that h(X_H) = h(X_G), which implies that X_G and X_H are finitely equivalent. The encoding and decoding algorithms for the stream version of ABS establish a bijection between X_G and X_H. We consider the case where p = 1/β with the golden mean β = (1 + √5)/2. Eventually we show that X_G and X_H are conjugate for l = 7, and that they are almost conjugate for l = 10.