From 21st century,it is hard for traditional storage and algorithm to provide service with high quality because of big data of communication which grows rapidly.Thus,cloud computing technology with relatively low cost...From 21st century,it is hard for traditional storage and algorithm to provide service with high quality because of big data of communication which grows rapidly.Thus,cloud computing technology with relatively low cost of hardware facilities is created.However,to guarantee the quality of service in the situation of the rapid growth of data volume,the energy consumption cost of cloud computing begins to exceed the hardware cost.In order to solve the problems mentioned above,this study briefly introduced the virtual machine and its energy consumption model in the mobile cloud environment,introduced the basic principle of the virtual machine migration strategy based on the artificial bee colony algorithm and then simulated the performance of processing strategy to big data of communication based on artificial bee colony algorithm in mobile cloud computing environment by CloudSim3.0 software,which was compared with the performance of two algorithms,resource management(RM)and genetic algorithm(GA).The results showed that the power consumption of the migration strategy based on the artificial bee colony algorithm was lower than the other two strategies,and there were fewer failed virtual machines under the same number of requests,which meant that the service quality was higher.展开更多
Situated at the intersection of technology and medicine,the Internet of Things(IoT)holds the promise of addressing some of healthcare's most pressing challenges,from medical error,to chronic drug shortages,to over...Situated at the intersection of technology and medicine,the Internet of Things(IoT)holds the promise of addressing some of healthcare's most pressing challenges,from medical error,to chronic drug shortages,to overburdened hospital systems,to dealing with the COVID-19 pandemic.However,despite considerable recent technological advances,the pace of successful implementation of promising IoT healthcare initiatives has been slow.To inspire more productive collaboration,we present here a simple—but surprisingly underrated—problemoriented approach to developing healthcare technologies.To further assist in this effort,we reviewed the various commercial,regulatory,social/cultural,and technological factors in the development of the IoT.We propose that fog computing—a technological paradigm wherein the burden of computing is shifted from a centralized cloud server closer to the data source—offers the greatest promise for building a robust and scalable healthcare IoT ecosystem.To this end,we explore the key enabling technologies that underpin the fog architecture,from the sensing layer all the way up to the cloud.It is our hope that ongoing advances in sensing,communications,cryptography,storage,machine learning,and artificial intelligence will be leveraged in meaningful ways to generate unprecedented medical intelligence and thus drive improvements in the health of many people.展开更多
The 5 th generation(5 G)mobile networks has been put into services across a number of markets,which aims at providing subscribers with high bit rates,low latency,high capacity,many new services and vertical applicatio...The 5 th generation(5 G)mobile networks has been put into services across a number of markets,which aims at providing subscribers with high bit rates,low latency,high capacity,many new services and vertical applications.Therefore the research and development on 6 G have been put on the agenda.Regarding demands and characteristics of future 6 G,artificial intelligence(A),big data(B)and cloud computing(C)will play indispensable roles in achieving the highest efficiency and the largest benefits.Interestingly,the initials of these three aspects remind us the significance of vitamin ABC to human body.In this article we specifically expound on the three elements of ABC and relationships in between.We analyze the basic characteristics of wireless big data(WBD)and the corresponding technical action in A and C,which are the high dimensional feature and spatial separation,the predictive ability,and the characteristics of knowledge.Based on the abilities of WBD,a new learning approach for wireless AI called knowledge+data-driven deep learning(KD-DL)method,and a layered computing architecture of mobile network integrating cloud/edge/terminal computing,is proposed,and their achievable efficiency is discussed.These progress will be conducive to the development of future 6 G.展开更多
The application of artificial intelligence(AI)technology in the medical field has experienced a long history of development.In turn,some long-standing points and challenges in the medical field have also prompted dive...The application of artificial intelligence(AI)technology in the medical field has experienced a long history of development.In turn,some long-standing points and challenges in the medical field have also prompted diverse research teams to continue to explore AI in depth.With the development of advanced technologies such as the Internet of Things(IoT),cloud computing,big data,and 5G mobile networks,AI technology has been more widely adopted in the medical field.In addition,the in-depth integration of AI and IoT technology enables the gradual improvement of medical diagnosis and treatment capabilities so as to provide services to the public in a more effective way.In this work,we examine the technical basis of IoT,cloud computing,big data analysis and machine learning involved in clinical medicine,combined with concepts of specific algorithms such as activity recognition,behavior recognition,anomaly detection,assistant decision-making system,to describe the scenario-based applications of remote diagnosis and treatment collaboration,neonatal intensive care unit,cardiology intensive care unit,emergency first aid,venous thromboembolism,monitoring nursing,image-assisted diagnosis,etc.We also systematically summarize the application of AI and IoT in clinical medicine,analyze the main challenges thereof,and comment on the trends and future developments in this field.展开更多
Computer science concept and ability is crucial to modern information technology.As a basic computer science education,computational thinking has become one of the first courses for college students and the foundation...Computer science concept and ability is crucial to modern information technology.As a basic computer science education,computational thinking has become one of the first courses for college students and the foundation for training for non-computer professionals.Computational thinking is a way of thinking that students in all majors should master.In the process of teaching,students learn to use computational thinking to solve professional and technical problems and make good use of computer’s powerful tools.It is one of the major themes of recent teaching research.We set course objectives from issues-driven and correspond each class to the module objectives,so that the focus of course content is clear.The learning clues for the students are clear,which is conducive to the cultivation and improvement of computational thinking.展开更多
文摘From 21st century,it is hard for traditional storage and algorithm to provide service with high quality because of big data of communication which grows rapidly.Thus,cloud computing technology with relatively low cost of hardware facilities is created.However,to guarantee the quality of service in the situation of the rapid growth of data volume,the energy consumption cost of cloud computing begins to exceed the hardware cost.In order to solve the problems mentioned above,this study briefly introduced the virtual machine and its energy consumption model in the mobile cloud environment,introduced the basic principle of the virtual machine migration strategy based on the artificial bee colony algorithm and then simulated the performance of processing strategy to big data of communication based on artificial bee colony algorithm in mobile cloud computing environment by CloudSim3.0 software,which was compared with the performance of two algorithms,resource management(RM)and genetic algorithm(GA).The results showed that the power consumption of the migration strategy based on the artificial bee colony algorithm was lower than the other two strategies,and there were fewer failed virtual machines under the same number of requests,which meant that the service quality was higher.
基金supported in part by a grant from the Victoria-Jiangsu Program for Technology and Innovation Research and Development。
文摘Situated at the intersection of technology and medicine,the Internet of Things(IoT)holds the promise of addressing some of healthcare's most pressing challenges,from medical error,to chronic drug shortages,to overburdened hospital systems,to dealing with the COVID-19 pandemic.However,despite considerable recent technological advances,the pace of successful implementation of promising IoT healthcare initiatives has been slow.To inspire more productive collaboration,we present here a simple—but surprisingly underrated—problemoriented approach to developing healthcare technologies.To further assist in this effort,we reviewed the various commercial,regulatory,social/cultural,and technological factors in the development of the IoT.We propose that fog computing—a technological paradigm wherein the burden of computing is shifted from a centralized cloud server closer to the data source—offers the greatest promise for building a robust and scalable healthcare IoT ecosystem.To this end,we explore the key enabling technologies that underpin the fog architecture,from the sensing layer all the way up to the cloud.It is our hope that ongoing advances in sensing,communications,cryptography,storage,machine learning,and artificial intelligence will be leveraged in meaningful ways to generate unprecedented medical intelligence and thus drive improvements in the health of many people.
基金supported by Key Program of Natural Science Foundation of China(Grant No.61631018)Anhui Provincial Natural Science Foundation(Grant No.1908085MF177)Huawei Technology Innovative Research(YBN2018095087)。
文摘The 5 th generation(5 G)mobile networks has been put into services across a number of markets,which aims at providing subscribers with high bit rates,low latency,high capacity,many new services and vertical applications.Therefore the research and development on 6 G have been put on the agenda.Regarding demands and characteristics of future 6 G,artificial intelligence(A),big data(B)and cloud computing(C)will play indispensable roles in achieving the highest efficiency and the largest benefits.Interestingly,the initials of these three aspects remind us the significance of vitamin ABC to human body.In this article we specifically expound on the three elements of ABC and relationships in between.We analyze the basic characteristics of wireless big data(WBD)and the corresponding technical action in A and C,which are the high dimensional feature and spatial separation,the predictive ability,and the characteristics of knowledge.Based on the abilities of WBD,a new learning approach for wireless AI called knowledge+data-driven deep learning(KD-DL)method,and a layered computing architecture of mobile network integrating cloud/edge/terminal computing,is proposed,and their achievable efficiency is discussed.These progress will be conducive to the development of future 6 G.
文摘The application of artificial intelligence(AI)technology in the medical field has experienced a long history of development.In turn,some long-standing points and challenges in the medical field have also prompted diverse research teams to continue to explore AI in depth.With the development of advanced technologies such as the Internet of Things(IoT),cloud computing,big data,and 5G mobile networks,AI technology has been more widely adopted in the medical field.In addition,the in-depth integration of AI and IoT technology enables the gradual improvement of medical diagnosis and treatment capabilities so as to provide services to the public in a more effective way.In this work,we examine the technical basis of IoT,cloud computing,big data analysis and machine learning involved in clinical medicine,combined with concepts of specific algorithms such as activity recognition,behavior recognition,anomaly detection,assistant decision-making system,to describe the scenario-based applications of remote diagnosis and treatment collaboration,neonatal intensive care unit,cardiology intensive care unit,emergency first aid,venous thromboembolism,monitoring nursing,image-assisted diagnosis,etc.We also systematically summarize the application of AI and IoT in clinical medicine,analyze the main challenges thereof,and comment on the trends and future developments in this field.
基金supported in part by the Production,Teaching and Research Project of the Ministry of Education in 2022.
文摘Computer science concept and ability is crucial to modern information technology.As a basic computer science education,computational thinking has become one of the first courses for college students and the foundation for training for non-computer professionals.Computational thinking is a way of thinking that students in all majors should master.In the process of teaching,students learn to use computational thinking to solve professional and technical problems and make good use of computer’s powerful tools.It is one of the major themes of recent teaching research.We set course objectives from issues-driven and correspond each class to the module objectives,so that the focus of course content is clear.The learning clues for the students are clear,which is conducive to the cultivation and improvement of computational thinking.
