The multi-attribute group decision making method based on the interval grey linguistic variables weighted harmonic aggregation operators

With respect to the characteristics of fuzziness, complexity and uncertainty for many group-decision making problems in real world, the paper proposes a novel method based on the interval grey linguistic variables hybrid weighted harmonic aggregation operators to solve the multiple attribute group decision making problems in which the attribute values and the weights take the form of the interval grey linguistic variables. In the approach, the relative concepts and the operation rules of interval grey linguistic variables are defined, and some operators (such as interval grey linguistic weighted harmonic aggregation (IGLWHA) operator, interval grey linguistic ordered weighted harmonic aggregation (IGLOWHA) operator, and interval grey linguistic hybrid weighted harmonic aggregation (IGLHWHA) operator) are proposed to solve the group decision making problems. The computational results from an illustrative example have shown that the proposed approach is feasible and effective for the group-decision making problems

A Regulatable Blockchain Transaction Model with Privacy Protection

Blockchain is a decentralized distributed ledger technology. The public chain represented by Bitcoin and Ethereum only realizes the limited anonymity of user identity, and the transaction amount is open to the whole network, resulting in user privacy leakage. Based on the existing anonymous technology, the concealment of the sender, receiver, amount of the transaction, and does not disclose any information, which makes the supervision difficult. Therefore, the design of blockchain scheme with privacy protection and supervision functions is of great significance. In this paper, a blockchain transaction model with both privacy and supervision function is proposed. It uses probability encryption to realize the hiding of the true identity of the blockchain transaction, and uses the commitment scheme and zero-knowledge proof technology to realize the privacy protection and guarantee legitimacy verification of the transaction. With the use of encryption technology, the regulators can supervise blockchain transactions without storing the users' information, which greatly reduces the pressure on storage, computing and key management. In addition, it does not rely on specific consensus mechanism and can be used as an independent module. The security performance analysis shows that the proposed scheme has great practicability and has potential application in many fields

What Went Wrong? Closing the Sim-to-Real Gap via Differentiable Causal Discovery

Training control policies in simulation is more appealing than on real robots directly, as it allows for exploring diverse states in a safe and efficient manner. Yet, robot simulators inevitably exhibit disparities from the real world, yielding inaccuracies that manifest as the simulation-to-real gap. Existing literature has proposed to close this gap by actively modifying specific simulator parameters to align the simulated data with real-world observations. However, the set of tunable parameters is usually manually selected to reduce the search space in a case-by-case manner, which is hard to scale up for complex systems and requires extensive domain knowledge. To address the scalability issue and automate the parameter-tuning process, we introduce an approach that aligns the simulator with the real world by discovering the causal relationship between the environment parameters and the sim-to-real gap. Concretely, our method learns a differentiable mapping from the environment parameters to the differences between simulated and real-world robot-object trajectories. This mapping is governed by a simultaneously-learned causal graph to help prune the search space of parameters, provide better interpretability, and improve generalization. We perform experiments to achieve both sim-to-sim and sim-to-real transfer, and show that our method has significant improvements in trajectory alignment and task success rate over strong baselines in a challenging manipulation task

Effects of aluminum diffusion on the adhesive behavior of the Ni(111)/Cr2O3(0001) interface: First principle study

AbstractDensity functional theory was employed to investigate the structure and properties of Ni/Cr2O3 and Ni/Al2O3/Cr2O3. The O-terminated Ni(111)/Cr2O3(0001) interface was firstly found to be the most stable configuration. Based on this construction, the effects of the Al diffusion at the Ni/Cr2O3 interface were further studied. The results of total energies indicate that Al atoms originating from Ni slab prefer to diffuse into Cr2O3 slab through the interface, resulting in the formation of alumina at the Ni/Cr2O3 interface. Due to the presence of Al atoms, there was an amazing increase in the work of adhesion, whereas the Ni/Al2O3/Cr2O3 interface showed the strongest stability. Moreover, this calculated work well agrees with the reported experimental results

Modelling and experimental testing of an optical synchronisation beacon designed for high‐loss satellite quantum communication

Long‐distance free space quantum key distribution based on CubeSats can be used to establish global quantum secure communication networks, with potential commercial applications benefitting from the low cost of its design and launch. Detecting single‐photon level optical pulses sent from space requires highly accurate and robust timing systems to pick out signals from the noise. For such high‐loss applications, we envisage a low‐repetition (sub‐MHz) beacon laser emitting short (ns) high‐peak‐power pulses from which interpolated quantum signal arrival windows can be derived. We firstly study theoretically the effects of jitter on the efficiency of gating quantum signals including all important jitter sources, and then experimentally investigated it by changing the clock jitter, and the result shows that the greater jitter will reduce the gating rate of the signal. The experimental interpolation error is tested against loss under laboratory conditions giving results close to our model. We also found that the jitter introduced by the Doppler effect can be ignored with a repetition rate larger than 1 kHz. This model can be directly used for the performance analysis and optimisation of all quantum and non‐quantum systems using similar synchronisation schemes over terrestrial free space or fibre

Enhanced tensile ductility and strength of electrodeposited ultrafine-grained nickel with a desired bimodal microstructure

This work aims to use surfactant-assisted direct current electrodeposition technique to prepare four types of bimodal nickel, under different current densities. Bimodal Ni is obtained with different grain size and spatial distribution of CG and UFG areas showing a big disparity in mechanical properties. As a result of small population of coarse-grained surrounded by quite a lot of ultrafine-grained forming a unique shell-and-core bimodal structure, bimodal one present the best comprehensive mechanical properties with an ultrahigh tensile strength (similar to 847 MPa) and a considerable plastic strain (similar to 16.7%). Deformation initial, bimodal structures display more positive strain hardening to meaningful strains than unimodal structure of UFG and CG. Particularly bimodal one work-hardening rate is the highest thanks to its structure (UFG occupy 76.7% in total number fraction) and the distribution of growth twins. Growth twins in this article are referred to Sigma 3(111) coherent twins playing an important role in improving high strength, enhancing uniform plastic deformation ability