In this paper, we propose a neural network-based in-loop filter (NNLF) for versatile video coding (VVC) intra coding based on a dual-branch collaborative architecture. The proposed NNLF leverages spatial-frequency feature fusion to effectively learn multi-type input features and adopts a dual-branch collaborative architecture to process global quantization features from the quantization parameter (QP) map branch and local artifacts from the prediction/partition frame branch separately. In the former branch, the multi-scale refinement block, driven by wavelet transform convolution (WTConv), suppresses inter-block brightness differences by operating on frequency-decomposed subbands. In the latter branch, the progressive residual enhancement network restores texture discontinuities in the predicted regions through a dual-attention mechanism. Moreover, the adaptive fusion block alleviates input feature conflicts based on two pixel-wise attention maps by learning the global features from the QP map and the local features from the prediction and partition frames, enabling an effective fusion of complementary information. Experimental results show that the proposed NNLF achieves average Bjøntegaard Delta (BD)-rate gains of 8.43% (Y), 22.16% (U), and 23.00% (V) in peak signal-to-noise ratio (PSNR) over the VVC test model (VTM)-11.0_neural network-based video coding (NNVC)-3.0 anchor under All Intra (AI) configuration. The code is available at: https://github.com/Xidian-Media-Lab/Dual-Branch-NNLF .

This study is rooted in a generalized regression neural network (GRNN) and undeformed grinding chips to predict the grinding force of spiral bevel gears. Firstly, establish a grinding force model for an individual abrasive particle, and integrate it with the dynamic number of abrasive particles in the grinding wheel to obtain a spiral bevel gear grinding force model based on undeformed grinding chips. Secondly, using the duplex spread blade design technique, the spiral conical gear blank geometric dimensions, machine tool adjustment parameters, and tool specifications are calculated, and the simulation of milling and grinding is carried out in three-dimensional solid modeling software. The undeformed chips and related parameters are obtained through Boolean intersection. Due to the complexity of calculation and simulation in the development procedure of spiral bevel gears, the GRNN is established to predict the undeformed grinding chip parameters of non-simulated gears. Finally, each group's comprehensive coefficient of cutting and friction forces were calculated through grinding experiments at different generating motion speeds. Predict these coefficients through experimental data. The results showed that the maximum standard deviation between the expected grinding force and the experimental value was 3.3260, which verifies the method's effectiveness. The GRNN algorithm can help select process parameters more reasonably, avoid tooth surface burns, and improve machining efficiency.

Database watermark is an effective solution to the piracy and data leakage problems. It is recognized as the final defense line in zero-trust architecture. Most of the traditional watermark schemes are based on carrier modification, which is difficult to achieve robustness while maintaining data quality. A new distortion free relational data watermark scheme is proposed, which guarantees data quality. Firstly, a watermark encoding algorithm is applied to combine bits in the data with the watermark information to generate auxiliary data, which is then stored. In the watermark extraction stage, the watermark decoding algorithm extracts the watermark information from the auxiliary data. The watermark capacity is greatly increased by encoding at least one attribute of each tuple. This does not modify the original data in any way and avoids the data distortion problems associated with traditional schemes. The experimental results show that the proposed scheme is more robust than traditional robust watermark schemes.

A location privacy protection method based on route constraints is proposed for the use of location-based services in vehicular networks. This scheme proposes a system architecture based on semi trusted third-party services, which stores user private information separately on three parties. Even if attackers acquire some information, they still cannot obtain the complete private information of the user, thus effective resists single point attacks from attackers. In addition, a dummy location selection algorithm based on route constraints and query history is proposed, which improves the privacy protection by maximizing physical dispersion, and location difference. The proposed method does not require any reliable third-party server, which can protect vehicle location privacy against inference attacks using route information, service record, and other auxiliary information. Security and cost analysis was conducted on the proposed method. The experimental results showed that this method can ensure the uncertainty and physical dispersion of dummy locations, improving the effectiveness of dummy locations, and effectively protect vehicle location privacy.

Abstract Byzantine broadcast is a fundamental primitive in distributed computing. A highly efficient Byzantine broadcast protocol, motivated by the real‐world performance of practical state machine replication protocols, is increasingly needed. This article focuses on the state‐of‐the‐art partially synchronous Byzantine broadcast protocol proposed by Abraham et al. (PODC’21), which achieves optimal good‐case latency of two rounds and optimal resilience of n ≥ 5 f − 1 in this setting. Each step of the protocol is analysed, and then improved by cutting down the number of messages required to be collected and transmitted in the heaviest step of the protocol by about half , without adding any extra cost. This benefits from a new property, named “spread”, that we identify and extract from the original protocol. It helps us to eliminate non‐essential work in its view‐change procedure. The authors also show that no further reduction is possible without violating security. A prototype is implemented and the performances of improved and original protocols are evaluated in the same environment. The results show that our improvement can achieve about 50% lower communication cost and 40% shorter latency at a scale of 100 replicas. The latency gap becomes wider as the scale further increases.

The revelations about massive surveillance have created significant interest in algorithm substitution attack (ASA), where an honest implementation of a cryptographic primitive is replaced by a subverted one which can help “big brother" to break cryptographic security while generating output indistinguishable from the honest output. The current known ASAs on public-key cryptography are either dedicated for a type of concrete constructions with specific internal, or restrictive when applying to the real-word cryptographic standards (Ateniese et al., ACM CCS’15; Russell et al., ACM CCS’17; Chen et al., ASIACRYPT’20). In this paper, we first present a practical undetectable substitution for a general randomized algorithm with certain structure such that the randomness can be revealed to the big brother. Then, instantiating this randomized algorithm, we present a series of ASAs on core primitives in public-key cryptography including public-key encryption, key encapsulation mechanism, key exchange, and digital signature. In particular, our ASAs are universal in the sense that they do not rely on the internal description of the underlying cryptographic algorithm. Moreover, our ASAs are also practical since they can affect not only the widely deployed cryptographic standards, but also the ongoing NIST post-quantum standards.

To enhance the lower limbs' rehabilitation training of stroke patients, in this article, a deterministic adaptive robust control with control gain parameters optimized by a novel cooperative game theory is proposed for the two-degree-of-freedom (DOF) lower limb exoskeleton robot system (LLERs) with uncertainties and external disturbances. On the one hand, the deterministic adaptive robust control put forward will guarantee the uniform boundedness and uniform ultimate boundedness of gait constraint deviation and parameter estimation error. On the other hand, for uncertainties and external disturbance (possibly fast time-varying), which will arise in the two-DOF LLERs inevitably, we suppose that these uncertainties and disturbances are bounded, and their bounds are lying within the fuzzy sets, which can be characterized by membership functions; with such descriptions and control performance analysis, a novel cooperative game with two players participated will be formulated to seek the Pareto optimal solutions for the control gains of deterministic adaptive robust control proposed, and furthermore, the existence of optimal solutions is also shown by invoking a numerical technique. Eventually, the simulation results presented have verified the effectiveness of our proposed methodology on improving rehabilitation training of lower limbs.

In this paper, we consider the potential influences on energy efficiency when Device to Device (D2D) communication is introduced to small cell network with sleep scheme. To begin with, we obtain the optimal sleep strategy for small cells, then we define parameters sleep ratio (SR) and maximum sleeping cell (MSC) to describe system dormant situation. Furthermore, parameters λ and θ are defined to indicate the D2D offloading ratio as well as geographic distribution of D2D users. We show that D2D communication will always be energy beneficial to the base station side. However, when considering the overall energy consumption (users included), D2D Assisted Sleep Mode (DASM) may cost more energy than D2D Forbidden Sleep Mode (DFSM). We demonstrate that to obtain the λ scope where DASM is energy efficient, it equals to calculate the positive range of a quadratic function f(θ,λ). Therefore, D2D scheduling scheme should be self-adaptive according to the f(θ, λ) curve to keep the network energy efficient. The analysis method in this paper should be universal regardless of the specific system models.

Orthogonal experimental design (OED) is a well-known method in statistical experiment which aims to reduce the testing complexity. This paper tries applying OED to reduce the computational complexity in Multiple-input Multiple-output (MIMO) detection. Several times of sorted QR decomposition (SQRD) algorithm are applied firstly to get the diverse solutions. Then a subspace is constructed with the diverse results. Inside the subspace, OED shows its potential and value in reducing the computational complexity compares with the exhaustive method. The proposed QR-OED MIMO scheme provides nearly 8 dB gain compared with the traditional sorted QRD while the minimal computational complexity needed is only 3.7% compared with exhaustive method for the 6×6 MIMO system and 4-QAM modulation scheme.

With Device to Device (D2D) user equipment (DUE) sharing the same resources with traditional cellular user equipment (CUE), intra-cell interference is becoming a challenging issue nowadays in D2D underlaying network. However, due to the lack of convexity, globally optimal resource sharing scheme is generally unattainable. In this paper, we propose a genetic algorithm (GA) based user matching scheme (GAM) with optimal power allocation (OPA) to achieve the multi-dimension optimization. Firstly, we demonstrate that the optimal power allocation between DUE and CUE can be obtained by searching several finite solution sets in the feasible region boundries. Secondly, genetic algorithm is applied to obtain the near-optimal user matching in the whole network scope. Simulation results show that the GA based scheme can achieve 30Mbps system throughput gain comparing to the traditional greedy searching, while with a limited complexity increase.

Device to Device (D2D) underlaying cellular networks have drawn a lot of attention recently, in both Long Term Evolution (LTE) standardization as well as academic research, with its huge potential in increasing the system capacity. However, intra-cell interference is quite a challenging issue since D2D user equipment (DUE) may share the same resources with the traditional cellular user equipment (CUE). Moreover, due to the lack of convexity, globally optimal sharing strategy is generally unattainable. In this paper, we apply bipartite matching strategy from graph theory to optimize the resource allocation in D2D underlay network. Two different situations are considered in detail, namely optimal resource allocation with fixed power transmission (FPT) and optimal resource allocation with uplink power controlled transmission (PCT). Practical constraints such as minimum spectral efficiency and maximum transmit power limitations are also considered in the optimization. Simulations and analyses show that the proposed Bipartite Matching based Allocation (BMA) can improve the system capacity significantly comparing to those traditional methods.

The world is witnessing a tremendous increase in data demands which is subject to the new emerging technologies, applications and services. 60 GHz communication network is one of such technology, claiming data rate in multi-gigabits. In this paper, we propose a scheduling algorithm for device-to-device 60 GHz network having directional antennas. The proposed algorithm utilizes the vertex coloring scheme and is optimized to improve system throughput. A threshold minimum distance between conflicting flows is used to keep the accumulative interference limited. Also, when there are conflicts among different flows, those with better data rate prospects will be scheduled priorly. Simulation results show that our scheme has brought significant improvement to system throughput almost by 19% and average flow number per slot is improved by 12%, as compared to other scheduling algorithms.

To deal with the shrink of Picocell Downlink (DL) coverage areas, the concept of Cell Range Expansion (CRE) has been proposed, in which a positive value is added to the DL Reference Signal Received Power (RSRP) of picocell pilot signals.Although CRE will expand DL picocell footprint, it may also lead to severe DL inter-cell interference from macrocells since some picocell User Equipments (UEs) are not connected to the cells that provide the strongest RSRP. In this paper, we propose a new coordinated interference management scheme for macrocell-picocell Heterogeneous Network (HetNet) to improve the signal quality of picocell UEs. The proposed method is to coordinate frequency and power resources within a set of resource allocation restrictions. Based on the Third Generation Partnership Project (3GPP) LTE-Advanced (LTE-A) standardization, system level simulation results show that compared with alternative approaches, the proposed method can mitigate outages, improve cell-edge UEs' performance and bring a significant increase in overall system throughput.

A novel Multiple-input Multiple-output (MIMO) detection scheme based on orthogonal experimental design (OED) is proposed in this paper. By exploiting the initial solutions given by linear detection and non-linear detection algorithms, a searching subspace is constructed to obtain additional performance gain. Exhaustive searching method is optimal in the subspace, but with quite high complexity. Then OED, which is widely used in chemical experiments and statistics, is applied to reduce the computational complexity. The minimal required complexity of OED-MIMO is only 6.25% needed but just with insignificantly performance lost compared with exhaustive method for the 8×8 MIMO system and 16-QAM modulation scheme. The proposed OED-MIMO scheme provides nearly 10 dB gain compared with MMSE and 5 dB gain with ZF-VBLAST.