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In this article, a method of multi-connection load compensation and load information calculation for an upper-limb exoskeleton is proposed based on a six-axis force/torque sensor installed between the exoskeleton and the end effector. The proposed load compensation method uses a mounted sensor to measure the force and torque between the exoskeleton and load of different connections and adds a compensator to the controller to compensate the component caused by the load in the human-robot interaction force, so that the human-robot interaction force is only used to operate the exoskeleton. Therefore, the operator can manipulate the exoskeleton with the same interaction force to lift loads of different weights with a passive or fixed connection, and the human-robot interaction force is minimized. Moreover, the proposed load information calculation method can calculate the weight of the load and the position of its center of gravity relative to the exoskeleton and end effector accurately, which is necessary for acquiring the upper-limb exoskeleton center of gravity and stability control of whole-body exoskeleton. In order to verify the effectiveness of the proposed method, we performed load handling and operational stability experiments. The experimental results showed that the proposed method realized the expected function.

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Active worms, a category of self-replicating malicious programs which could spread in an automated fashion and flood particular Peer-to-Peer (P2P) networks within very short time, have drawn significant attention. However, only limited number of studies focus on propagation model of active worms with fair consideration of P2P nodes' dynamic features consisting of P2P churn, random quarantine, regular immunization, dynamic fragmentation and etc. This paper proposes three propagation models of active worms under dynamic P2P environment, conducts a mathematical analysis on the propagation of active worms under presented models and provides extensive numerical studies to the impact of relevant parameters on active worms' propagation speed under dynamic P2P environment. Models presented in this paper are simple, effective and thus applicable for defending against active worms in real P2P networks.

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