Nerve injury can cause lower limb paralysis and gait disorder. Currently lower limb rehabilitation exoskeleton robots used in the hospitals need more power to correct abnormal motor patterns of stroke patients’ legs. These gait rehabilitation robots are powered by cumbersome and bulky electric motors, which provides a poor user experience. A newly developed gait rehabilitation exoskeleton robot actuated by low-cost and lightweight pneumatic artificial muscles (PAMs) is presented in this research. A model-free proxy-based sliding mode control (PSMC) strategy and a model-based chattering mitigation robust variable control (CRVC) strategy were developed and first applied in rehabilitation trainings, respectively. As the dynamic response of PAM due to the compressed air is low, an innovative intention identification control strategy was taken in active trainings by the use of the subject’s intention indirectly through the estimation of the interaction force between the subject’s leg and the exoskeleton. The proposed intention identification strategy was verified by treadmill-based gait training experiments.

Abstract. With the continuous development of Web technology and the sustained popularization of the Internet, the security problems of the Web has been attracting more and more attention from the network workers. According to the OWASP (Open Web Application Security Project), XSS (CrossSite Scripting) has been among the top three vulnerabilities in a number of threats. Therefore, it is very meaningful to design XSS vulnerability automatic mining tools. Crawler, as a web data scratching tool, has been favored by search engine workers. In this paper, we introduce a dynamic parallel crawler aiming for XSS vulnerability detection, and the basic principle of XSS. Based on them, we designed an efficient XSS detection tool. Finally, an experiment shows that our tools can detect XSS vulnerabilities efficiently.

Abstract. Cross-site scripting attacks has always been one of the most common attacks to the front-end network applications. With the popularity of HTML5, the security of Email systems is facing new challenges. In this paper, we propose a new approach which utilizes HTML5 new tags and new attributes to construct storage-type XSS attack vectors. Based on this method, we have tested several domestic and foreign common mailbox and detected six HTML5-based XSS vulnerabilities. The final evaluation results show that our method can detect storage-type XSS vulnerabilities based on HTML5 effectively.