Recent studies have identified subchondral bone deterioration as a critical factor in the degeneration of the overlying articular cartilage.This relationship is linked to abnormalities in the subchondral bone microenv...Recent studies have identified subchondral bone deterioration as a critical factor in the degeneration of the overlying articular cartilage.This relationship is linked to abnormalities in the subchondral bone microenvironment and remodelling processes during osteoarthritis(OA).These processes include mechanical stimulation signals,chondrocyte apoptosis,matrix degradation,H-type vessel formation,and a complex balance between osteoclasts and osteoblasts,as well as the growth of sensory nerve axons.1 Osteoclast overactivity and vascular invasion in subchondral bones are closely associated with abnormal bone remodelling and the progression of OA.2.展开更多
In recent years,with the rapid development of Internet and hardware technologies,the number of Internet of things(IoT)devices has grown exponentially.However,IoT devices are constrained by power consumption,making the...In recent years,with the rapid development of Internet and hardware technologies,the number of Internet of things(IoT)devices has grown exponentially.However,IoT devices are constrained by power consumption,making the security of IoT vulnerable.Malware such as Botnets and Worms poses significant security threats to users and enterprises alike.Deep learning models have demonstrated strong performance in various tasks across different domains,leading to their application in malicious software detection.Nevertheless,due to the power constraints of IoT devices,the well-performanced large models are not suitable for IoT malware detection.In this paper we propose a malware detection method based on Markov images and MobileNet,offering a cost-effective,efficient,and high-performing solution for malware detection.Additionally,this paper innovatively analyzes the robustness of opcode sequences.展开更多
基金supported by the National Natural Science Foundation of China(Nos.82372490,81972123,82172508)Fundamental Research Funds for the Central Universities(No.2015SCU04A40)+3 种基金The Innovative Spark Project of Sichuan University(No.2018SCUH0034)Chengdu Science and Technology Bureau Project(No.2019-YF05-00090-SN)1.3.5 Project for Disciplines of Excellence of West China Hospital Sichuan University(Nos.ZYJC21030,ZY2017301)1·3·5 project for disciplines of excellence-Clinical Research Incubation Project,West China Hospital,Sichuan University(No.2019HXFH039).
文摘Recent studies have identified subchondral bone deterioration as a critical factor in the degeneration of the overlying articular cartilage.This relationship is linked to abnormalities in the subchondral bone microenvironment and remodelling processes during osteoarthritis(OA).These processes include mechanical stimulation signals,chondrocyte apoptosis,matrix degradation,H-type vessel formation,and a complex balance between osteoclasts and osteoblasts,as well as the growth of sensory nerve axons.1 Osteoclast overactivity and vascular invasion in subchondral bones are closely associated with abnormal bone remodelling and the progression of OA.2.
基金This work was supported by the National Key R&D Program of China under Grant 2020YFB1807503 and NSFC Fund under Grant U20A20156.
文摘In recent years,with the rapid development of Internet and hardware technologies,the number of Internet of things(IoT)devices has grown exponentially.However,IoT devices are constrained by power consumption,making the security of IoT vulnerable.Malware such as Botnets and Worms poses significant security threats to users and enterprises alike.Deep learning models have demonstrated strong performance in various tasks across different domains,leading to their application in malicious software detection.Nevertheless,due to the power constraints of IoT devices,the well-performanced large models are not suitable for IoT malware detection.In this paper we propose a malware detection method based on Markov images and MobileNet,offering a cost-effective,efficient,and high-performing solution for malware detection.Additionally,this paper innovatively analyzes the robustness of opcode sequences.
