Digitalization is a bridge for TCM striding towards information age

Digitalization is a bridge for traditional Chinese medicine(TCM)striding towards information age.Application of digital technologies such as computers and mathematical statistics methods has played a revolutionary role in TCM diagnosis and syndrome standardization studies.

New Copyright Challenges and Opportunities for Academic Librarians in Hong Kong in the Digital Information Age

1 Introduction High-speed networking can now deliver Information tomillions of users in seconds.Users In turn can download thedata in electronic format or just print them out with a fewstrokes of the keyboard.The data can be easily saved,reorganized and modified electronocally.While informationtechnology provides fast and easy ways to distributeinformation,it also presents challenges.Easy access tocopyrighted materials is resulting in the unauthorizedreproduction of all kinds of information,forcing info...

Impact of the World's New Technological Revolution on Economic Development and Educational Reform in the Information Age

The fourth industrial revolution of human society is also known as the"world's new technological revolution,"which has brought human society into the information age and has had an extremely important impact on economic development and educational reform.In the information age,economic development and wealth creation are dominated by the acquisition,mastery,distribution,and utilization of information instead of capital.Therefore,the cultivation of talents is very important,and educational reform is imperative with the rise of the world's new technological revolution.

Impact of the World’s New Technological Revolution on Economic Development and Educational Reform in the Information Age

The fourth industrial revolution of human society is also known as the“world’s new technological revolution,”which has brought human society into the information age and has had an extremely important impact on economic development and educational reform.In the information age,economic development and wealth creation are dominated by the acquisition,mastery,distribution,and utilization of information instead of capital.Therefore,the cultivation of talents is very important,and educational reform is imperative with the rise of the world’s new technological revolution.

Age of Information for Short-Packet Covert Communication with Time Modulated Retrodirective Array

In this paper,the covert age of information(CAoI),which characterizes the timeliness and covertness performance of communication,is first investigated in the short-packet covert communication with time modulated retrodirective array(TMRDA).Specifically,the TMRDA is designed to maximize the antenna gain in the target direction while the side lobe is sufficiently suppressed.On this basis,the covertness constraint and CAoI are derived in closed form.To facilitate the covert transmission design,the transmit power and block-length are jointly optimized to minimize the CAoI,which demonstrates the trade-off between covertness and timelessness.Our results illustrate that there exists an optimal block-length that yields the minimum CAoI,and the presented optimization results can achieve enhanced performance compared with the fixed block-length case.Additionally,we observe that smaller beam pointing error at Bob leads to improvements in CAoI.

Age of Loop Information with Flexible Transmission Enabled Communication and Control Co-Design in Industrial IoT

Precise and low-latency information transmission through communication systems is essential in the Industrial Internet of Things(IIoT).However,in an industrial system,there is always a coupling relationship between the control and communication components.To improve the system's overall performance,exploring the co-design of communication and control systems is crucial.In this work,we propose a new metric±Age of Loop Information with Flexible Transmission(AoLI-FT),which dynamically adjusts the maximum number of uplink(UL)and downlink(DL)transmission rounds,thus enhancing reliability while ensuring timeliness.Our goal is to explore the relationship between AoLI-FT,reliability,and control convergence rate,and to design optimal blocklengths for UL and DL that achieve the desired control convergence rate.To address this issue,we first derive a closed-form expression for the upper bound of AoLI-FT.Subsequently,we establish a relationship between communication reliability and control convergence rates using a Lyapunov-like function.Finally,we introduce an iterative alternating algorithm to determine the optimal communication and control parameters.The numerical results demonstrate the significant performance advantages of our proposed communication and control co-design strategy in terms of latency and control cost.

Age of Information Based User Scheduling and Data Assignment in Multi-User Mobile Edge Computing Networks:An Online Algorithm

This paper investigates the age of information(AoI)-based multi-user mobile edge computing(MEC)network with partial offloading mode.The weighted sum AoI(WSA)is first analyzed and derived,and then a WSA minimization problem is formulated by jointly optimizing the user scheduling and data assignment.Due to the non-analytic expression of the WSA w.r.t.the optimization variables and the unknowability of future network information,the problem cannot be solved with known solution methods.Therefore,an online Joint Partial Offloading and User Scheduling Optimization(JPOUSO)algorithm is proposed by transforming the original problem into a single-slot data assignment subproblem and a single-slot user scheduling sub-problem and solving the two sub-problems separately.We analyze the computational complexity of the presented JPO-USO algorithm,which is of O(N),with N being the number of users.Simulation results show that the proposed JPO-USO algorithm is able to achieve better AoI performance compared with various baseline methods.It is shown that both the user’s data assignment and the user’s AoI should be jointly taken into account to decrease the system WSA when scheduling users.

Minimizing Age of Information in the Uplink Multi-User Networks via Dynamic Bandwidth Allocation

Improving the information freshness is critical for the monitoring and controlling applications in the cellular Internet of Things(IoT).In this paper,we are interested in optimizing the bandwidth allocation dynamically to improve the information freshness of the short packet based uplink status updates,which is characterized by a recently proposed metric,age of information(Ao I).We first design a status update scheme with channel distribution information(CDI).By relaxing the hard bandwidth constraint and introducing a Lagrangian multiplier,we first decouple the multi-MTCD bandwidth allocation problem into a single MTCD Markov decision process(MDP).Under the MDP framework,after variable substitution,we obtain the single-MTCD status update scheme by solving a linear programming problem.Then,we adjust the Lagrangian multiplier to make the obtained scheme satisfy the relaxed bandwidth constraint.Finally,a greedy policy is built on the proposed scheme to adjust the bandwidth allocation in each slot to satisfy the hard bandwidth constraint.In the unknown environment without CDI,we further design a bandwidth allocation scheme which only maximizes the expected sum Ao I drop within each time slot.Simulation results show that in terms of AoI,the proposed schemes outperform the benchmark schemes.

Age-Driven Joint Sampling and Non-Slot Based Scheduling for Industrial Internet of Things

Effective control of time-sensitive industrial applications depends on the real-time transmission of data from underlying sensors.Quantifying the data freshness through age of information(AoI),in this paper,we jointly design sampling and non-slot based scheduling policies to minimize the maximum time-average age of information(MAoI)among sensors with the constraints of average energy cost and finite queue stability.To overcome the intractability involving high couplings of such a complex stochastic process,we first focus on the single-sensor time-average AoI optimization problem and convert the constrained Markov decision process(CMDP)into an unconstrained Markov decision process(MDP)by the Lagrangian method.With the infinite-time average energy and AoI expression expended as the Bellman equation,the singlesensor time-average AoI optimization problem can be approached through the steady-state distribution probability.Further,we propose a low-complexity sub-optimal sampling and semi-distributed scheduling scheme for the multi-sensor scenario.The simulation results show that the proposed scheme reduces the MAoI significantly while achieving a balance between the sampling rate and service rate for multiple sensors.

Vehicular Beacon Broadcast Scheduling Based on Age of Information(AoI)

Vehicular beaconing plays an important role to facilitate various applications in the paradigm of Internet of Vehicles(IoV). Due to high dynamic and resource limitation in IoV, how to schedule the vehicular beacon broadcast is challenging, especially in dense scenarios. In this paper, we investigate the beacon broadcast scheduling problem considering the Age of Information(AoI). We first propose an algorithm minimizing the expected sum of AoI considering the limited communication resource and vehicle mobility. Then the performance of the proposed algorithm is analyzed. With the proposed algorithm, the optimal solution can be obtained under certain conditions. Extensive simulations are conducted to verify the efficiency, effectiveness and fairness of the proposed solution.

The prospects for Higher Vocational computer Education in the development of information technology age

Computer technology is one of the main technologies of the information society, the development of computer education satisfies for requirements to science, the world and the future, and it is an important part of students＇ quality education, it is of great significance to improve the scientific and cultural level of the students, to promote the teaching content modernization of education and teaching reform, to improve the quality of education and the level of management.

Information freshness optimization of multiple status update streams in Internet of things:Generation rate control and service rate reservation

The Internet of things(IoT)has become a key infrastructure providing up-to-date and fresh information for policy analysis and decision-making of upper-layer applications.However,there are limited sensing and communication resources in IoT devices,which significantly affects the timeliness and freshness of the updated status.This work proposes two schemes,namely,the generation rate control and service rate reservation schemes,to improve the overall information freshness of multiple status update streams at the receiver.Specifically,using the recently proposed Age of Information(AoI)as the metric for evaluating information freshness,we characterized the overall information freshness,i.e.,the overall average AoI at the receiver for both schemes,by considering the urgency difference of status update and streams.Both schemes for status updates and streams,respectively,were formulated as two optimization problems.We proved that both problems are convex and the optimal generation and service rates for different streams are found by the standard convex optimization algorithm.Moreover,we proposed both approximate optimal generation and approximate optimal service rate for fast deployment in heavy and light load cases.Numerical results verify the theoretical findings and accuracy of the proposed approximate solutions,guiding the design and deployment of IoT.

Preliminary Analysis of the Protection of Privacy in the Information Network Age

The development and appli- cation of modern computer information and network technology is a double- edged sword. On the one hand, thanks to the rapid and convenient spread and exchange of computer- ized information and the compressed time and space on the Internet, computerized information plays a positive role in many areas like the economy, culture, education, sci- ence and technology, and politics. On the other hand, it also leads to various online rights infringements： citizens＇ individual information is revealed online; personal comput- ers are hacked; and online shopping lists are copied. Many Internet users worry about these problems to some extent. Especially in recent years, as information technology has devel- oped rapidly, people＇s online privacy rights have faced unprecedented challenges. How to strengthen pro- tection of online individual privacy has become an important challenge to the healthy development of informa- tion networks.

Age-of-Information-Aware Federated Learning

Federated learning(FL)is an emerging privacy-preserving distributed computing paradigm,enabling numerous clients to collaboratively train machine learning models without the necessity of transmitting clients’private datasets to the central server.Unlike most existing research where the local datasets of clients are assumed to be unchanged over time throughout the whole FL process,our study addresses such scenarios in this paper where clients’datasets need to be updated periodically,and the server can incentivize clients to employ as fresh as possible datasets for local model training.Our primary objective is to design a client selection strategy to minimize the loss of the global model for FL loss within a constrained budget.To this end,we introduce the concept of“Age of Information”(AoI)to quantitatively assess the freshness of local datasets and conduct a theoretical analysis of the convergence bound in our AoI-aware FL system.Based on the convergence bound,we further formulate our problem as a restless multi-armed bandit(RMAB)problem.Next,we relax the RMAB problem and apply the Lagrangian Dual approach to decouple it into multiple subproblems.Finally,we propose a Whittle’s Index Based Client Selection(WICS)algorithm to determine the set of selected clients.In addition,comprehensive simulations substantiate that the proposed algorithm can effectively reduce training loss and enhance the learning accuracy compared with some state-of-the-art methods.

Age-of-information-aware PI controller for load frequency control

Open communication system in modern power systems brings concern about information staleness which may cause power system frequency instability.The information staleness is often characterized by communication delay.However,communication delay is a packet-centered metric and cannot reflect the requirement of information freshness for load frequency control(LFC).This paper introduces the age of information(AoI),which is more compre-hensive and informative than the conventional communication delay modeling method.An LFC controller and com-munication are integrated into the design for LFC performance improvement.An AoI-aware LFC model is formulated first,and considering each allowable update period of the smart sensor,different AoI-aware PI controllers are then designed according to the exponential decay rate.The right AoI-aware controller and update period are selected according to the degree of frequency fluctuation of the power system.Case studies are carried out on one-area and two-area power systems.The results show the superior performance of the AoI-aware controllers in comparison to the delay-dependent controllers.

Timely Updates in MEC-Assisted Status Update Systems: Joint Task Generation and Computation Offloading Scheme

Fresh status updates are vital to the efficient operation of network monitoring and real-time control applications. In this paper, we consider a mobile edge computing(MEC)-assisted status update system, where smart devices extract valuable status updates from sensed data to achieve timely awareness of the surroundings by exploiting computational resources at the device and edge server. To quantify the freshness of status updates obtained by executing computation tasks, we employ the concept of age of information(Ao I) to characterize the timeliness of status updates. To cope with the limited energy at devices, we investigate a joint task generation and computation offloading scheme under a given energy budget for minimizing the age of obtained status updates. The age minimization problem is modeled as a constrained Markov decision process(CMDP). To obtain the optimal policy, we derive the structural properties of the optimal deterministic policy and propose a lightweight structure-based status update algorithm in the case of known channel statistics. Moreover, we consider a more realistic scenario without prior knowledge of channel statistics, and propose a Q-learning-based status update algorithm to make online decisions. Simulation results show that the performance of our proposed algorithms is competitive when compared with existing schemes.

Freshness constraints of an age of information based event-triggered Kalman consensus filter algorithm over a wireless sensor network

This paper presents the design of a new event-triggered Kalman consensus filter(ET-KCF)algorithm for use over a wireless sensor network(WSN).This algorithm is based on information freshness,which is calculated as the age of information(Aol)of the sampled data.The proposed algorithm integrates the traditional event-triggered mechanism,information freshness calculation method,and Kalman consensus filter(KCF)algorithm to estimate the concentrations of pollutants in the aircraft more efficiently.The proposed method also considers the influence of data packet loss and the aircraft's loss of communication path over the WSN,and presents an Aol-freshness-based threshold selection method for the ET-KCF algorithm,which compares the packet Aol to the minimum average Aol of the system.This method can obviously reduce the energy consumption because the transmission of expired information is reduced.Finally,the convergence of the algorithm is proved using the Lyapunov stability theory and matrix theory.Simulation results show that this algorithm has better fault tolerance compared to the existing KCF and lower power consumption than other ET-KCFs.