Towards Practical Topology-Hiding Computation

\par Topology-hiding computation (THC) enables $n$ parties to perform a secure multiparty computation (MPC) protocol in an incomplete communication graph while keeping the communication graph hidden. The work of Akavia et al. (CRYPTO 2017 and JoC 2020) shown that THC is feasible for any graph. In this work, we focus on the efficiency of THC and give improvements for various tasks including broadcast, sum and general computation. We mainly consider THC on undirected cycles, but we also give two results for THC on general graphs. All of our results are derived in the presence of a passive adversary statically corrupting any number of parties. \par In the undirected cycles, the state-of-the-art topology-hiding broadcast (THB) protocol is the Akavia-Moran (AM) protocol of Akavia et al. (EUROCRYPT 2017). We give an optimization for the AM protocol such that the communication cost of broadcasting $O(\kappa)$ bits is reduced from $O(n^2\kappa^2)$ bits to $O(n^2\kappa)$ bits. We also consider the sum and general computation functionalities. Previous to our work, the only THC protocols realizing the sum and general computation functionalities are constructed by using THB to simulate point-to-point channels in an MPC protocol realizing the sum and general computation functionalities, respectively. By allowing the parties to know the exact value of the number of the parties (the AM protocol and our optimization only assume the parties know an upper bound of the number of the parties), we can derive more efficient THC protocols realizing these two functionalities. As a result, comparing with previous works, we reduce the communication cost by a factor of $O(n\kappa)$ for both the sum and general computation functionalities. \par As we have mentioned, we also get two results for THC on general graphs. The state-of-the-art THB protocol for general graphs is the Akavia-LaVigne-Moran (ALM) protocol of Akavia et al. (CRYPTO 2017 and JoC 2020). Our result is that our optimization for the AM protocol also applies to the ALM protocol and can reduce its communication cost by a factor of $O(\kappa)$. Moreover, we optimize the fully-homomorphic encryption (FHE) based GTHC protocol of LaVigne et al. (TCC 2018) and reduce its communication cost from $O(n^8\kappa^2)$ FHE ciphertexts and $O(n^5\kappa)$ FHE public keys to $O(n^6\kappa)$ FHE ciphertexts and $O(n^5\kappa)$ FHE public keys

On the Performance Trade-off of Distributed Integrated Sensing and Communication Networks

In this letter, we analyze the performance trade-off in distributed integrated sensing and communication (ISAC) networks. Specifically, with the aid of stochastic geometry theory, we derive the probability of detection of that of the coverage given user number. Based on the analytical derivations, we provide a quantitative description of the performance limits and the performance trade-off between sensing and communication in a distributed ISAC network under the given transmit power and bandwidth budget. Extensive simulations are conducted and the numerical results validate the accuracy of our derivations

Semantic Communications with Ordered Importance using ChatGPT

This letter proposes a novel semantic communication scheme with ordered importance (SCOI) using the chat generative pre-trained transformer (ChatGPT). In the proposed SCOI scheme, ChatGPT plays the role of a consulting assistant. Given a message to be transmitted, the transmitter first queries ChatGPT to output the importance order of each word. According to the importance order, the transmitter then performs an unequal error protection transmission strategy to make the transmission of essential words more reliable. Unlike the existing semantic communication schemes, SCOI is compatible with existing source-channel separation designs and can be directly embedded into current communication systems. Our experimental results show that both the transmission bit error rate (BER) of important words and the semantic loss measured by ChatGPT are much lower than the existing communication schemes

Robust Beamforming and Rate-Splitting Design for Next Generation Ultra-Reliable and Low-Latency Communications

The next generation ultra-reliable and low-latency communications (xURLLC) need novel design to provide satisfactory services to the emerging mission-critical applications. To improve the spectrum efficiency and enhance the robustness of xURLLC, this paper proposes a robust beamforming and rate-splitting design in the finite blocklength (FBL) regime for downlink multi-user multi-antenna xURLLC systems. In the design, adaptive rate-splitting is introduced to flexibly handle the complex inter-user interference and thus improve the spectrum efficiency. Taking the imperfection of the channel state information at the transmitter (CSIT) into consideration, a max-min user rate problem is formulated to optimize the common and private beamforming vectors and the rate-splitting vector under the premise of ensuring the requirements of transmission latency and reliability of all the users. The optimization problem is intractable due to the non-convexity of the constraint set and the infinite constraints caused by CSIT uncertainties. To solve it, we convert the infinite constraints into finite ones by the S-Procedure method and transform the original problem into a difference of convex (DC) programming. A constrained concave convex procedure (CCCP) and the Gaussian randomization based iterative algorithm is proposed to obtain a local minimum. Simulation results confirm the convergence, robustness and effectiveness of the proposed robust beamforming and rate-splitting design in the FBL regime. It is also shown that the proposed robust design achieves considerable performance gain in the worst user rate compared with existing transmission schemes under various blocklength and block error rate requirements.Comment: 12 pages, 9 figure

An Effective Surface Defect Classification Method Based on RepVGG with CBAM Attention Mechanism (RepVGG-CBAM) for Aluminum Profiles

The automatic classification of aluminum profile surface defects is of great significance in improving the surface quality of aluminum profiles in practical production. This classification is influenced by the small and unbalanced number of samples and lack of uniformity in the size and spatial distribution of aluminum profile surface defects. It is difficult to achieve high classification accuracy by directly using the current advanced classification algorithms. In this paper, digital image processing methods such as rotation, flipping, contrast, and luminance transformation were used to augment the number of samples and imitate the complex imaging environment in actual practice. A RepVGG with CBAM attention mechanism (RepVGG-CBAM) model was proposed and applied to classify ten types of aluminum profile surface defects. The classification accuracy reached 99.41%, in particular, the proposed method can perfectly classify six types of defects: concave line (cl), exposed bottom (eb), exposed corner bottom (ecb), mixed color (mc), non-conductivity (nc) and orange peel (op), with 100% precision, recall, and F1. Compared with the existing advanced classification algorithms VGG16, VGG19, ResNet34, ResNet50, ShuffleNet_v2, and basic RepVGG, our model is the best in terms of accuracy, macro precision, macro recall and macro F1, and the accuracy was improved by 4.85% over basic RepVGG. Finally, an ablation experiment proved that the classification ability was strongest when the CBAM attention mechanism was added following Stage 1 to Stage 4 of RepVGG. Overall, the method we proposed in this paper has a significant reference value for classifying aluminum profile surface defects

Microscopic characteristics of magnetorheological fluids subjected to magnetic fields

© 2020 Elsevier B.V. With the aim of studying the microscopic characteristics of a magnetorheological fluid (MRF) in a magnetic field, the theoretical analyses of the particles dynamics in a magnetic field are presented, and a model for the particle motion is proposed. Based on these analyses, a three-dimensional numerical simulation of the microstructure of MRFs in different magnetic fields is performed. Furthermore, the microstructures of the MRFs are investigated using industrial computed tomography (CT) imaging. The numerical simulation and industrial CT results indicate that the chain structure of the same MRF becomes more apparent as the magnetic field strength increases, and in the same external magnetic field, this chain structure also becomes more apparent with an increase in the particle volume fraction. The lengths of particle chains in different magnetic fields are also captured in the industrial CT experiments. When the magnetic field strength is 12 mT, the particle chains of the MRF with a particle volume fraction of 30% reach more than 10 mm in length, which bridge the inner diameter of the container, and the dense clusters-like structure is formed, the clusters-like structure becomes denser with an increase in magnetic field. Moreover, the particle chain lengths of MRF with high particle volume fractions increase sharply with the magnetic field. The experiments demonstrated that the industrial CT is an efficient method to study the microstructures of MRFs by providing particle distributions of MRFs more clearly and intuitively

Vibration control of a tunnel boring machine using adaptive magnetorheological damper

With a large number of tunnel boring machines (TBM) being used in various tunnel constructions, the vibration problem under complex geological conditions have become increasingly prominent. In order to solve the problem, this article investigates the application of an adaptive magnetorheological (MR) damper on the vibration reduction of a TBM. The MR damper could reduce the horizontal vibration of the TBM system and adjust its dragging force on the propulsive system under different geological conditions. The MR damper can also provide large enough damping force even under a small amplitude vibration, which is required by TBM. In this paper, an MR damper was designed, prototyped and its properties were tested by an MTS system, including its current-dependency, amplitude-dependency and frequency-dependency features. A scaled TBM system incorporated with the MR damper was built to evaluate the vibration reduction effectiveness of the MR damper on the TBM system. The experimental test results demonstrate that the displacement and the acceleration amplitudes of the TMB vibration could be reduced by 52.14% and 53.31%, respectively

Design and experimental evaluation of a new modular underactuated multi-fingered robot hand

© IMechE 2020. In this paper, a modular underactuated multi-fingered robot hand is proposed. The robot hand can be freely configured with different number and configuration of modular fingers according to the work needs. Driving motion is achieved by the rigid structure of the screw and the connecting rod. A finger-connecting mechanism is designed on the palm of the robot hand to meet the needs of modular finger’s installation, drive, rotation, and sensor connections. The fingertips are made of hollow rubber to enhance the stability of grasping. Details about the design of the robot hand and analysis of the robot kinematics and grasping process are described. Last, a prototype is developed, and a grab test is carried out. Experimental results demonstrate that the structure of proposed modular robot hand is reasonable, which enables the adaptability and flexibility of the modular robot hand to meet the requirements of various grasping modes in practice

An Adaptive Spatial-Temporal Local Feature Difference Method for Infrared Small-moving Target Detection

Detecting small moving targets accurately in infrared (IR) image sequences is a significant challenge. To address this problem, we propose a novel method called spatial-temporal local feature difference (STLFD) with adaptive background suppression (ABS). Our approach utilizes filters in the spatial and temporal domains and performs pixel-level ABS on the output to enhance the contrast between the target and the background. The proposed method comprises three steps. First, we obtain three temporal frame images based on the current frame image and extract two feature maps using the designed spatial domain and temporal domain filters. Next, we fuse the information of the spatial domain and temporal domain to produce the spatial-temporal feature maps and suppress noise using our pixel-level ABS module. Finally, we obtain the segmented binary map by applying a threshold. Our experimental results demonstrate that the proposed method outperforms existing state-of-the-art methods for infrared small-moving target detection