A novel type of hybrid ultrasonic motor using longitudinal and torsional vibration modes with side panels

A novel type of hybrid ultrasonic motor using longitudinal and torsional vibration modes is presented, which has four side panels uniformly distributed along the circumference of the stator cylinder. There is rectangle piezoelectric ceramics (PZTs) based on d31 effect bonded on both sides of each side panels, which can be used to convert the first bending vibration mode of the side panels into the second torsional vibration mode of the stator when the exciting voltage is applied. Meanwhile, there are rectangle PZTs based on d31 effect bonded on the surfaces of the stator cylinder between every two side panels, which can be used to excite the first longitudinal vibration mode of the stator. The simulation results using finite element method (FEM) software Workbench reveals the suitable polarization arrangement of PZTs and the final designed structure of the motor. The appearance size of the prototype is 28.2 mm×28.2 mm×68 mm, while the outer diameter of the stator cylinder is 20 mm. The major vibration and mechanical characteristics of the prototype have been measured. The working frequency of the prototype measured in experiment is around 43.12 kHz, which is consistent with the numerical results. When operating voltage of 350 Vp-p is applied, the no-load speed of the prototype is 103 rpm and the stalling torque is 48 mN·m

Risk Response for Municipal Solid Waste Crisis Using Ontology-Based Reasoning

Many cities in the world are besieged by municipal solid waste (MSW). MSW not only pollutes the ecological environment but can even induce a series of public safety crises. Risk response for MSW needs novel changes. This paper innovatively adopts the ideas and methods of semantic web ontology to build an ontology-based reasoning system for MSW risk response. Through the integration of crisis information and case resources in the field of MSW, combined with the reasoning ability of Semantic Web Rule Language (SWRL), a system of rule reasoning for risk transformation is constructed. Knowledge extraction and integration of MSW risk response can effectively excavate semantic correlation of crisis information along with key transformation points in the process of crisis evolution through rule reasoning. The results show that rule reasoning of transformation can effectively improve intelligent decision-making regarding MSW risk response

FedCut: A Spectral Analysis Framework for Reliable Detection of Byzantine Colluders

This paper proposes a general spectral analysis framework that thwarts a security risk in federated Learning caused by groups of malicious Byzantine attackers or colluders, who conspire to upload vicious model updates to severely debase global model performances. The proposed framework delineates the strong consistency and temporal coherence between Byzantine colluders' model updates from a spectral analysis lens, and, formulates the detection of Byzantine misbehaviours as a community detection problem in weighted graphs. The modified normalized graph cut is then utilized to discern attackers from benign participants. Moreover, the Spectral heuristics is adopted to make the detection robust against various attacks. The proposed Byzantine colluder resilient method, i.e., FedCut, is guaranteed to converge with bounded errors. Extensive experimental results under a variety of settings justify the superiority of FedCut, which demonstrates extremely robust model performance (MP) under various attacks. It was shown that FedCut's averaged MP is 2.1% to 16.5% better than that of the state of the art Byzantine-resilient methods. In terms of the worst-case model performance (MP), FedCut is 17.6% to 69.5% better than these methods

Non-clausal multi-ary alpha-generalized resolution calculus for a finite lattice-valued logic

Due to the need of the logical foundation for uncertain information processing, development of efficient automated reasoning system based on non-classical logics is always an active research area. The present paper focuses on the resolution-based automated reasoning theory in a many-valued logic with truth-values defined in a lattice-ordered many-valued algebraic structure - lattice implication algebras (LIA). Specifically, as a continuation and extension of the established work on binary resolution at a certain truth-value level α (called α-resolution), a non-clausal multi-ary α-generalized resolution calculus is introduced for a lattice-valued propositional logic LP(X) based on LIA, which is essentially a non-clausal generalized resolution avoiding reduction to normal clausal form. The new resolution calculus in LP(X) is then proved to be sound and complete. The concepts and theoretical results are further extended and established in the corresponding lattice-valued first-order logic LF(X) based on LIA