The mass communication model and interactive ritual chain theory,which serve as communication paradigms in the new media era,facilitate and enhance the synergy between the fields of social history of medicine and heal...The mass communication model and interactive ritual chain theory,which serve as communication paradigms in the new media era,facilitate and enhance the synergy between the fields of social history of medicine and health communication.This study employs a comprehensive framework based on the five elements of the mass communication model:information source,communication subject,communication object,message content,and post-communication feedback.Additionally,it incorporates the interactive ritual chain theory to examine the evolving dynamics and developmental trajectory of research in the social history of medicine during the new media era.Conclusively,this paper acknowledges the existing interaction gaps in the interaction between health communication and the social history of medicine research while outlining the challenges for fostering collaboration and proposing strategic optimizations for effective integration.展开更多
To fit in with the developing requirement of int and communication of protective relays, a protection egrated functions of protection measurement, control measurement and control system based on DeviceNet fieldbus is ...To fit in with the developing requirement of int and communication of protective relays, a protection egrated functions of protection measurement, control measurement and control system based on DeviceNet fieldbus is designed. The communication mechanism of DeviceNet is studied and data trigger modes, communication connection, message types and other key technologies are analyzed. The object modeling and device description of the device are realized too. Results of network test, dynamic simulation and test in the field indicate that this system can accomplish all the communication tasks in real time and can make precise response to every kind of faults of the motor, transformer, line and capacitor. Moreover, this system has higher measurement precision and better control capability.展开更多
BACKGROUND Severe pneumonia is a common severe respiratory infection worldwide,and its treatment is challenging,especially for patients in the intensive care unit(ICU).AIM To explore the effect of communication and co...BACKGROUND Severe pneumonia is a common severe respiratory infection worldwide,and its treatment is challenging,especially for patients in the intensive care unit(ICU).AIM To explore the effect of communication and collaboration between nursing teams on the treatment outcomes of patients with severe pneumonia in ICU.METHODS We retrospectively analyzed 60 patients with severe pneumonia who were treated at the ICU of the hospital between January 1,2021 and December 31,2023.We compared and analyzed the respiratory mechanical indexes[airway resistance(Raw),mean airway pressure(mPaw),peak pressure(PIP)],blood gas analysis indexes(arterial oxygen saturation,arterial oxygen partial pressure,and oxygenation index),and serum inflammatory factor levels[C-reactive protein(CRP),procalcitonin(PCT),cortisol(COR),and high mobility group protein B1(HMGB1)]of all patients before and after treatment.RESULTS Before treatment,there was no significant difference in respiratory mechanics index and blood gas analysis index between 2 groups(P>0.05).However,after treatment,the respiratory mechanical indexes of patients in both groups were significantly improved,and the improvement of Raw,mPaw,plateau pressure,PIP and other indexes in the combined group after communication and collaboration with the nursing team was significantly better than that in the single care group(P<0.05).The serum CRP and PCT levels of patients were significantly decreased,and the difference was statistically significant compared with that of nursing group alone(P<0.05).The levels of serum COR and HMGB1 before and after treatment were also significantly decreased between the two groups.CONCLUSION The communication and collaboration of the nursing team have a significant positive impact on respiratory mechanics indicators,blood gas analysis indicators and serum inflammatory factor levels in the treatment of severe pneumonia patients in ICU.展开更多
As an important mechanism in multi-agent interaction,communication can make agents form complex team relationships rather than constitute a simple set of multiple independent agents.However,the existing communication ...As an important mechanism in multi-agent interaction,communication can make agents form complex team relationships rather than constitute a simple set of multiple independent agents.However,the existing communication schemes can bring much timing redundancy and irrelevant messages,which seriously affects their practical application.To solve this problem,this paper proposes a targeted multiagent communication algorithm based on state control(SCTC).The SCTC uses a gating mechanism based on state control to reduce the timing redundancy of communication between agents and determines the interaction relationship between agents and the importance weight of a communication message through a series connection of hard-and self-attention mechanisms,realizing targeted communication message processing.In addition,by minimizing the difference between the fusion message generated from a real communication message of each agent and a fusion message generated from the buffered message,the correctness of the final action choice of the agent is ensured.Our evaluation using a challenging set of Star Craft II benchmarks indicates that the SCTC can significantly improve the learning performance and reduce the communication overhead between agents,thus ensuring better cooperation between agents.展开更多
As the maritime industry continues to thrive and maritime services diversify,the demand for highly reliable maritime communication systems has become increasingly prominent.However,harsh marine conditions pose signifi...As the maritime industry continues to thrive and maritime services diversify,the demand for highly reliable maritime communication systems has become increasingly prominent.However,harsh marine conditions pose significant challenges to communication systems.In this work,we propose a Maritime AutoEncoder(MAE)communication system based on Attention Mechanisms(AMs)and DenseBlock(namely AM-Dense-MAE).AM-Dense-MAE utilizes DenseBlock and long short-term memory to extract deep features and capture spatio-temporal relationships,addressing the issue of“long-term dependency”.Furthermore,the decoder incorporates spatial attention modules and convolutional block attention module to enhance the preservation of crucial information and suppress irrelevant data.We employ the Rician fading channel model to simulate maritime communication channels.A substantial volume of data is utilized for model training and parameter optimization.Simulation results demonstrate that,in comparison to the benchmarks,the proposed AM-Dense-MAE exhibits better block error rate performance under various signal-to-noise ratio conditions and showcases generalization capabilities across diverse parameter settings.展开更多
In order to make the information transmission more efficient and reliable in a digital communication channel with limited capacity, various encoding-decoding techniques have been proposed and widely applied in many br...In order to make the information transmission more efficient and reliable in a digital communication channel with limited capacity, various encoding-decoding techniques have been proposed and widely applied in many branches of the signal processing including digital communications, data compression,information encryption, etc. Recently, due to its promising application potentials in the networked systems(NSs), the analysis and synthesis issues of the NSs under various encoding-decoding schemes have stirred some research attention. However, because of the network-enhanced complexity caused by the limited network resources, it poses new challenges to the design of suitable encoding-decoding procedures to meet certain control or filtering performance for the NSs. In this survey paper, our aim is to present a comprehensive review of the encoding-decodingbased control and filtering problems for different types of NSs.First, some basic introduction with respect to the coding-decoding mechanism is presented in terms of its engineering insights,specific properties and theoretical formulations. Then, the recent representative research progress in the design of the encodingdecoding protocols for various control and filtering problems is discussed. Some possible further research topics are finally outlined for the encoding-decoding-based NSs.展开更多
As 5G becomes commercial,researchers have turned attention toward the Sixth-Generation(6G)network with the vision of connecting intelligence in a green energy-efficient manner.Federated learning triggers an upsurge of...As 5G becomes commercial,researchers have turned attention toward the Sixth-Generation(6G)network with the vision of connecting intelligence in a green energy-efficient manner.Federated learning triggers an upsurge of green intelligent services such as resources orchestration of communication infrastructures while preserving privacy and increasing communication efficiency.However,designing effective incentives in federated learning is challenging due to the dynamic available clients and the correlation between clients'contributions during the learning process.In this paper,we propose a dynamic incentive and reputation mechanism to improve energy efficiency and training performance of federated learning.The proposed incentive based on the Stackelberg game can timely adjust optimal energy consumption with changes in available clients during federated learning.Meanwhile,clients’contributions in reputation management are formulated based on the cooperative game to capture the correlation between tasks,which satisfies availability,fairness,and additivity.The simulation results show that the proposed scheme can significantly motivate high-performance clients to participate in federated learning and improve the accuracy and energy efficiency of the federated learning model.展开更多
For the past few decades,the internet of underwater things(IoUT)otained a lot of attention in mobile aquatic applications such as oceanography,diver network monitoring,unmanned underwater exploration,underwater survei...For the past few decades,the internet of underwater things(IoUT)otained a lot of attention in mobile aquatic applications such as oceanography,diver network monitoring,unmanned underwater exploration,underwater surveillance,location tracking system,etc.Most of the IoUT applications rely on acoustic medium.The current IoUT applications face difficulty in delivering a reliable communication system due to the various technical limitations of IoUT environment such as low data rate,attenuation,limited bandwidth,limited battery,limited memory,connectivity problem,etc.One of the significant applications of IoUT include monitoring underwater diver networks.In order to perform a reliable and energy-efficient communication system in the underwater diver networks,a smart underwater hybrid softwaredefined modem(UHSDM)for the mobile ad-hoc network was developed that is used for selecting the best channel/medium among acoustic,visible light communication(VLC),and infrared(IR)based on the criteria established within the system.However,due to the mobility of underwater divers,the developed UHSDMmeets the challenges such as connectivity errors,frequent link failure,transmission delay caused by re-routing,etc.During emergency,the divers are most at the risk of survival.To deal with diver mobility,connectivity,energy efficiency,and reducing the latency in ADN,a handover mechanism based on pre-built UHSDM is proposed in this paper.This paper focuses on(1)design of UHSDM for ADN(2)propose the channel selection mechanism in UHSDM for selecting the best medium for handover and(3)propose handover protocol inADN.The implementation result shows that the proposed mechanism can be used to find the new route for divers in advance and the latency can be reduced significantly.Additionally,this paper shows the real field experiment of air tests and underwater tests with various distances.This research will contribute much to the profit of researchers in underwater diver networks and underwater networks,for improving the quality of services(QoS)of underwater applications.展开更多
This article investigates the optimization of low latency and high reliability communication mechanisms in 5G URLLC scenarios.Firstly,the key features and challenges of 5G URLLC were outlined,followed by an in-depth a...This article investigates the optimization of low latency and high reliability communication mechanisms in 5G URLLC scenarios.Firstly,the key features and challenges of 5G URLLC were outlined,followed by an in-depth analysis of the implementation mechanisms for low latency and high reliability communication,including physical layer technology,network architecture optimization,and resource scheduling strategies.Through simulation experiments,the effectiveness of the optimization mechanism has been verified,significantly reducing latency and improving reliability.展开更多
With the increasing data volume of train on-board system,real-time performance has become the most critical factor to ensure the safety of train operation.Considering that standard Ethernet cannot meet the real-time r...With the increasing data volume of train on-board system,real-time performance has become the most critical factor to ensure the safety of train operation.Considering that standard Ethernet cannot meet the real-time requirement of existing train communication network(TCN),the time-sensitive network(TSN)technology for TCN is introduced.To solve the time-delay problem,an adaptive switch queue selection mechanism for traffic scheduling is proposed.Firstly,the topology model of TCN based on TSN and the traffic model are described.Then,the K shortest path routing algorithm based on load balancing provides the optimal routing for the scheduling process.Finally,the adaptive switch queue selection mechanism is introduced to solve the aggregation flow conflict problem effectively,queue resources are properly allocated,and the gate control list(GCL)of each frame in the queue is obtained.Experimental results show that compared with the traditional constraint model,the schedulability of the model with an adaptive switch queue selection mechanism increases by 33.0%,and the maximum end-to-end delay and network jitter decrease by 19.1%and 18.6%on average respectively.It can provide theoretical support and application reference for the real-time performance optimization of TCN based on TSN.展开更多
Ⅰ.INTRODUCTION There are increasing concerns over data privacy,with information and communication technology proceeding at a rapid pace and posing intrusive challenges.Recognition of minors'vulnerability and tran...Ⅰ.INTRODUCTION There are increasing concerns over data privacy,with information and communication technology proceeding at a rapid pace and posing intrusive challenges.Recognition of minors'vulnerability and transformation in their rights'protection occurred not far from where we stand at present.Such a combination breeds a new subject of exploring minors'personal data protection,among which the consent mechanism is highlighted.展开更多
The propagation of information in online social networks plays a critical role in modern life,and thus has been studied broadly.Researchers have proposed a series of propagation models,generally,which use a single tra...The propagation of information in online social networks plays a critical role in modern life,and thus has been studied broadly.Researchers have proposed a series of propagation models,generally,which use a single transition probability or consider factors such as content and time to describe the way how a user activates her/his neighbors.However,the research on the mechanism how social ties between users play roles in propagation process is still limited.Specifically,comprehensive summary of factors which affect user’s decision whether to share neighbor’s content was lacked in existing works,so that the existing models failed to clearly describe the process a user be activated by a neighbor.To this end,in this paper,we analyze the close correspondence between social tie in propagation process and communication channel,thus we propose to exploit the communication channel to describe the information propagation process between users,and design a social tie channel(STC)model.The model can naturally incorporate many factors affecting the information propagation through edges such as content topic and user preference,and thus can effectively capture the user behavior and relationship characteristics which indicate the property of a social tie.Extensive experiments conducted on two real-world datasets demonstrate the effectiveness of our model on content sharing prediction between users.展开更多
To study the fluid dynamic response mechanism under the working condition of water injection well borehole,based on the microelement analysis of fluid mechanics and the classical theory of hydrodynamics,a fluid microe...To study the fluid dynamic response mechanism under the working condition of water injection well borehole,based on the microelement analysis of fluid mechanics and the classical theory of hydrodynamics,a fluid microelement pressure-flow rate relationship model is built to derive and solve the dynamic distribution of fluid pressure and flow rate in the space of well borehole.Combined with the production data of a typical deviated well in China,numerical simulations and analyses are carried out to analyze the dynamic distribution of wellbore pressure at different injection pressures and injection volumes,the delayed and attenuated characteristics of fluid transmission in tube,and the dynamic distribution of wellbore pressure amplitude under the fluctuation of wellhead pressure.The pressure loss along the wellbore has nothing to do with the absolute pressure,and the design of the coding and decoding scheme for wave code communication doesn’t need to consider the absolute pressure during injecting.When the injection pressure is constant,the higher the injection flow rate at the wellhead,the larger the pressure loss along the wellbore.The fluid wave signal delay amplitude mainly depends on the length of the wellbore.The smaller the tubing diameter,the larger the fluid wave signal attenuation amplitude.The higher the target wave code amplitude(differential pressure identification root mean square)generated at the same well depth,the greater the wellhead pressure wave amplitude required to overcome the wellbore pressure loss.展开更多
Against the backdrop of in-depth globalization and the rise of cultural mutual learning,the international communication of China’s Intangible Cultural Heritage(ICH)has become a key vehicle for enhancing China’s cult...Against the backdrop of in-depth globalization and the rise of cultural mutual learning,the international communication of China’s Intangible Cultural Heritage(ICH)has become a key vehicle for enhancing China’s cultural soft power and engaging in global cultural dialogue.However,in cross-cultural contexts,this communication faces structural dilemmas at multiple levels.From a cross-cultural perspective,this study proposes targeted solutions to address these dilemmas.The ultimate goal is to promote the transformation of China’s ICH international communication from“symbolic display”to“meaning sharing”and from“cultural output”to“value resonance”,thereby enhancing the effectiveness of cross-cultural communication and advancing the global recognition of China’s ICH.展开更多
Astrocytes are the most abundant glial cells in the central nervous system;they participate in crucial biological processes,maintain brain structure,and regulate nervous system function.Exosomes are cell-derived extra...Astrocytes are the most abundant glial cells in the central nervous system;they participate in crucial biological processes,maintain brain structure,and regulate nervous system function.Exosomes are cell-derived extracellular vesicles containing various bioactive molecules including proteins,peptides,nucleotides,and lipids secreted from their cellular sources.Increasing evidence shows that exosomes participate in a communication network in the nervous system,in which astrocyte-derived exosomes play important roles.In this review,we have summarized the effects of exosomes targeting astrocytes and the astrocyte-derived exosomes targeting other cell types in the central nervous system.We also discuss the potential research directions of the exosome-based communication network in the nervous system.The exosome-based intercellular communication focused on astrocytes is of great significance to the biological and/or pathological processes in different conditions in the brain.New strategies may be developed for the diagnosis and treatment of neurological disorders by focusing on astrocytes as the central cells and utilizing exosomes as communication mediators.展开更多
Satellite communication systems are facing serious electromagnetic interference,and interference signal recognition is a crucial foundation for targeted anti-interference.In this paper,we propose a novel interference ...Satellite communication systems are facing serious electromagnetic interference,and interference signal recognition is a crucial foundation for targeted anti-interference.In this paper,we propose a novel interference recognition algorithm called HDCGD-CBAM,which adopts the time-frequency images(TFIs)of signals to effectively extract the temporal and spectral characteristics.In the proposed method,we improve the Convolutional Long Short-Term Memory Deep Neural Network(CLDNN)in two ways.First,the simpler Gate Recurrent Unit(GRU)is used instead of the Long Short-Term Memory(LSTM),reducing model parameters while maintaining the recognition accuracy.Second,we replace convolutional layers with hybrid dilated convolution(HDC)to expand the receptive field of feature maps,which captures the correlation of time-frequency data on a larger spatial scale.Additionally,Convolutional Block Attention Module(CBAM)is introduced before and after the HDC layers to strengthen the extraction of critical features and improve the recognition performance.The experiment results show that the HDCGD-CBAM model significantly outper-forms existing methods in terms of recognition accuracy and complexity.When Jamming-to-Signal Ratio(JSR)varies from-30dB to 10dB,it achieves an average accuracy of 78.7%and outperforms the CLDNN by 7.29%while reducing the Floating Point Operations(FLOPs)by 79.8%to 114.75M.Moreover,the proposed model has fewer parameters with 301k compared to several state-of-the-art methods.展开更多
This paper investigates the consensus control of multi-agent systems(MASs) with constrained input using the dynamic event-triggered mechanism(ETM).Consider the MASs with small-scale networks where a centralized dynami...This paper investigates the consensus control of multi-agent systems(MASs) with constrained input using the dynamic event-triggered mechanism(ETM).Consider the MASs with small-scale networks where a centralized dynamic ETM with global information of the MASs is first designed.Then,a distributed dynamic ETM which only uses local information is developed for the MASs with large-scale networks.It is shown that the semi-global consensus of the MASs can be achieved by the designed bounded control protocol where the Zeno phenomenon is eliminated by a designable minimum inter-event time.In addition,it is easier to find a trade-off between the convergence rate and the minimum inter-event time by an adjustable parameter.Furthermore,the results are extended to regional consensus of the MASs with the bounded control protocol.Numerical simulations show the effectiveness of the proposed approach.展开更多
Artificial Intelligence (AI) is transforming organizational dynamics, and revolutionizing corporate leadership practices. This research paper delves into the question of how AI influences corporate leadership, examini...Artificial Intelligence (AI) is transforming organizational dynamics, and revolutionizing corporate leadership practices. This research paper delves into the question of how AI influences corporate leadership, examining both its advantages and disadvantages. Positive impacts of AI are evident in communication, feedback systems, tracking mechanisms, and decision-making processes within organizations. AI-powered communication tools, as exemplified by Slack, facilitate seamless collaboration, transcending geographical barriers. Feedback systems, like Adobe’s Performance Management System, employ AI algorithms to provide personalized development opportunities, enhancing employee growth. AI-based tracking systems optimize resource allocation, as exemplified by studies like “AI-Based Tracking Systems: Enhancing Efficiency and Accountability.” Additionally, AI-powered decision support, demonstrated during the COVID-19 pandemic, showcases the capability to navigate complex challenges and maintain resilience. However, AI adoption poses challenges in human resources, potentially leading to job displacement and necessitating upskilling efforts. Managing AI errors becomes crucial, as illustrated by instances like Amazon’s biased recruiting tool. Data privacy concerns also arise, emphasizing the need for robust security measures. The proposed solution suggests leveraging Local Machine Learning Models (LLMs) to address data privacy issues. Approaches such as federated learning, on-device learning, differential privacy, and homomorphic encryption offer promising strategies. By exploring the evolving dynamics of AI and leadership, this research advocates for responsible AI adoption and proposes LLMs as a potential solution, fostering a balanced integration of AI benefits while mitigating associated risks in corporate settings.展开更多
The progression of tumors is heavily influenced by mechanical properties of their microenvironment.In this work,we applied micropatterned models with varying distances and shapes to investigate the differences between...The progression of tumors is heavily influenced by mechanical properties of their microenvironment.In this work,we applied micropatterned models with varying distances and shapes to investigate the differences between metastatic MDA-MB-231 and non-metastatic MCF-7 breast cancer cells in reconfiguring extracellular matrix to promote cell migration induced by cell mechanics.Both cancer cells were able to rearrange type I collagen(COL)to form fibre threads,in which MDA-MB-231 consistently migrated more rapidly than MCF-7,ranging from geometrical square arrays with different spacings to complex polygonal models.MDA-MB-231 displayed higher capability of reorganizing fibre bundles at longer distance(800μm).Further looking for differences in cell molecular mechanisms,siRNA knockdown inhibiting either integrinβ1 or Piezo1 decreased fibre assembly and reduced the difference in COL remodeling and migration between two cancer cells.MDA-MB-231 showed inhibited migration with integrin knockdown,whereas scattering migration with Piezo1 knockdown,indicating cells losing directional mechanosensation.After inhibiting junctional E-cadherin with siRNA,MCF-7 cells migrated faster,resulting in reduced difference in comparison to MDA-MB-231 that didn't express E-cadherin.In summary,this work has explored the biomechanical differences between metastatic and non-metastatic breast cancer cells regarding COL fibre matrix remodeling and cell movements.The significant differences in E-cadherin expression in the two breast cancer cells had an effect on cell migrations.The results of this study provide research approaches for evaluating therapeutic effort on breast cancer.展开更多
基金University of Science and Technology of China Quality Project History of Medicine(2023YCZX02)Digital Museum Construction Project of Chinese Centre for Disease Control and Prevention(BB2110240080)The National Key R&D project granted by the Ministry of Science and Technology(2018YFA0902400).
文摘The mass communication model and interactive ritual chain theory,which serve as communication paradigms in the new media era,facilitate and enhance the synergy between the fields of social history of medicine and health communication.This study employs a comprehensive framework based on the five elements of the mass communication model:information source,communication subject,communication object,message content,and post-communication feedback.Additionally,it incorporates the interactive ritual chain theory to examine the evolving dynamics and developmental trajectory of research in the social history of medicine during the new media era.Conclusively,this paper acknowledges the existing interaction gaps in the interaction between health communication and the social history of medicine research while outlining the challenges for fostering collaboration and proposing strategic optimizations for effective integration.
文摘To fit in with the developing requirement of int and communication of protective relays, a protection egrated functions of protection measurement, control measurement and control system based on DeviceNet fieldbus is designed. The communication mechanism of DeviceNet is studied and data trigger modes, communication connection, message types and other key technologies are analyzed. The object modeling and device description of the device are realized too. Results of network test, dynamic simulation and test in the field indicate that this system can accomplish all the communication tasks in real time and can make precise response to every kind of faults of the motor, transformer, line and capacitor. Moreover, this system has higher measurement precision and better control capability.
文摘BACKGROUND Severe pneumonia is a common severe respiratory infection worldwide,and its treatment is challenging,especially for patients in the intensive care unit(ICU).AIM To explore the effect of communication and collaboration between nursing teams on the treatment outcomes of patients with severe pneumonia in ICU.METHODS We retrospectively analyzed 60 patients with severe pneumonia who were treated at the ICU of the hospital between January 1,2021 and December 31,2023.We compared and analyzed the respiratory mechanical indexes[airway resistance(Raw),mean airway pressure(mPaw),peak pressure(PIP)],blood gas analysis indexes(arterial oxygen saturation,arterial oxygen partial pressure,and oxygenation index),and serum inflammatory factor levels[C-reactive protein(CRP),procalcitonin(PCT),cortisol(COR),and high mobility group protein B1(HMGB1)]of all patients before and after treatment.RESULTS Before treatment,there was no significant difference in respiratory mechanics index and blood gas analysis index between 2 groups(P>0.05).However,after treatment,the respiratory mechanical indexes of patients in both groups were significantly improved,and the improvement of Raw,mPaw,plateau pressure,PIP and other indexes in the combined group after communication and collaboration with the nursing team was significantly better than that in the single care group(P<0.05).The serum CRP and PCT levels of patients were significantly decreased,and the difference was statistically significant compared with that of nursing group alone(P<0.05).The levels of serum COR and HMGB1 before and after treatment were also significantly decreased between the two groups.CONCLUSION The communication and collaboration of the nursing team have a significant positive impact on respiratory mechanics indicators,blood gas analysis indicators and serum inflammatory factor levels in the treatment of severe pneumonia patients in ICU.
文摘As an important mechanism in multi-agent interaction,communication can make agents form complex team relationships rather than constitute a simple set of multiple independent agents.However,the existing communication schemes can bring much timing redundancy and irrelevant messages,which seriously affects their practical application.To solve this problem,this paper proposes a targeted multiagent communication algorithm based on state control(SCTC).The SCTC uses a gating mechanism based on state control to reduce the timing redundancy of communication between agents and determines the interaction relationship between agents and the importance weight of a communication message through a series connection of hard-and self-attention mechanisms,realizing targeted communication message processing.In addition,by minimizing the difference between the fusion message generated from a real communication message of each agent and a fusion message generated from the buffered message,the correctness of the final action choice of the agent is ensured.Our evaluation using a challenging set of Star Craft II benchmarks indicates that the SCTC can significantly improve the learning performance and reduce the communication overhead between agents,thus ensuring better cooperation between agents.
基金supported by the National Natural Science Foundation of China(Nos.51939001 and 62371085)the Fundamental Research Funds for the Central Universities(No.3132023514).
文摘As the maritime industry continues to thrive and maritime services diversify,the demand for highly reliable maritime communication systems has become increasingly prominent.However,harsh marine conditions pose significant challenges to communication systems.In this work,we propose a Maritime AutoEncoder(MAE)communication system based on Attention Mechanisms(AMs)and DenseBlock(namely AM-Dense-MAE).AM-Dense-MAE utilizes DenseBlock and long short-term memory to extract deep features and capture spatio-temporal relationships,addressing the issue of“long-term dependency”.Furthermore,the decoder incorporates spatial attention modules and convolutional block attention module to enhance the preservation of crucial information and suppress irrelevant data.We employ the Rician fading channel model to simulate maritime communication channels.A substantial volume of data is utilized for model training and parameter optimization.Simulation results demonstrate that,in comparison to the benchmarks,the proposed AM-Dense-MAE exhibits better block error rate performance under various signal-to-noise ratio conditions and showcases generalization capabilities across diverse parameter settings.
基金supported in part by the Royal Society of the UK,the Nationa Natural Science,Foundation of China(61329301,61374039)the Program for Capability Construction of Shanghai Provincial Universities(15550502500)the Alexander von Humboldt Foundation of Germany
文摘In order to make the information transmission more efficient and reliable in a digital communication channel with limited capacity, various encoding-decoding techniques have been proposed and widely applied in many branches of the signal processing including digital communications, data compression,information encryption, etc. Recently, due to its promising application potentials in the networked systems(NSs), the analysis and synthesis issues of the NSs under various encoding-decoding schemes have stirred some research attention. However, because of the network-enhanced complexity caused by the limited network resources, it poses new challenges to the design of suitable encoding-decoding procedures to meet certain control or filtering performance for the NSs. In this survey paper, our aim is to present a comprehensive review of the encoding-decodingbased control and filtering problems for different types of NSs.First, some basic introduction with respect to the coding-decoding mechanism is presented in terms of its engineering insights,specific properties and theoretical formulations. Then, the recent representative research progress in the design of the encodingdecoding protocols for various control and filtering problems is discussed. Some possible further research topics are finally outlined for the encoding-decoding-based NSs.
文摘As 5G becomes commercial,researchers have turned attention toward the Sixth-Generation(6G)network with the vision of connecting intelligence in a green energy-efficient manner.Federated learning triggers an upsurge of green intelligent services such as resources orchestration of communication infrastructures while preserving privacy and increasing communication efficiency.However,designing effective incentives in federated learning is challenging due to the dynamic available clients and the correlation between clients'contributions during the learning process.In this paper,we propose a dynamic incentive and reputation mechanism to improve energy efficiency and training performance of federated learning.The proposed incentive based on the Stackelberg game can timely adjust optimal energy consumption with changes in available clients during federated learning.Meanwhile,clients’contributions in reputation management are formulated based on the cooperative game to capture the correlation between tasks,which satisfies availability,fairness,and additivity.The simulation results show that the proposed scheme can significantly motivate high-performance clients to participate in federated learning and improve the accuracy and energy efficiency of the federated learning model.
基金This research was a part of the project titled“Development of the wide-area underwater mobile communication systems”funded by the Ministry of Oceans and Fisheries,Korea.
文摘For the past few decades,the internet of underwater things(IoUT)otained a lot of attention in mobile aquatic applications such as oceanography,diver network monitoring,unmanned underwater exploration,underwater surveillance,location tracking system,etc.Most of the IoUT applications rely on acoustic medium.The current IoUT applications face difficulty in delivering a reliable communication system due to the various technical limitations of IoUT environment such as low data rate,attenuation,limited bandwidth,limited battery,limited memory,connectivity problem,etc.One of the significant applications of IoUT include monitoring underwater diver networks.In order to perform a reliable and energy-efficient communication system in the underwater diver networks,a smart underwater hybrid softwaredefined modem(UHSDM)for the mobile ad-hoc network was developed that is used for selecting the best channel/medium among acoustic,visible light communication(VLC),and infrared(IR)based on the criteria established within the system.However,due to the mobility of underwater divers,the developed UHSDMmeets the challenges such as connectivity errors,frequent link failure,transmission delay caused by re-routing,etc.During emergency,the divers are most at the risk of survival.To deal with diver mobility,connectivity,energy efficiency,and reducing the latency in ADN,a handover mechanism based on pre-built UHSDM is proposed in this paper.This paper focuses on(1)design of UHSDM for ADN(2)propose the channel selection mechanism in UHSDM for selecting the best medium for handover and(3)propose handover protocol inADN.The implementation result shows that the proposed mechanism can be used to find the new route for divers in advance and the latency can be reduced significantly.Additionally,this paper shows the real field experiment of air tests and underwater tests with various distances.This research will contribute much to the profit of researchers in underwater diver networks and underwater networks,for improving the quality of services(QoS)of underwater applications.
文摘This article investigates the optimization of low latency and high reliability communication mechanisms in 5G URLLC scenarios.Firstly,the key features and challenges of 5G URLLC were outlined,followed by an in-depth analysis of the implementation mechanisms for low latency and high reliability communication,including physical layer technology,network architecture optimization,and resource scheduling strategies.Through simulation experiments,the effectiveness of the optimization mechanism has been verified,significantly reducing latency and improving reliability.
基金supported by the National Natural Science Foundation of China(52072081)Major Project of Science and Technology of Guangxi Province of China(Guike AB23075209)+2 种基金Guangxi Manufacturing Systems and Advanced Manufacturing Technology Key Laboratory Director Fund(24050-44-S015)Innovation Project of Guangxi Graduate Education(YCSW2024135)Major Talent Project in Guangxi Zhuang Autonomous Region。
文摘With the increasing data volume of train on-board system,real-time performance has become the most critical factor to ensure the safety of train operation.Considering that standard Ethernet cannot meet the real-time requirement of existing train communication network(TCN),the time-sensitive network(TSN)technology for TCN is introduced.To solve the time-delay problem,an adaptive switch queue selection mechanism for traffic scheduling is proposed.Firstly,the topology model of TCN based on TSN and the traffic model are described.Then,the K shortest path routing algorithm based on load balancing provides the optimal routing for the scheduling process.Finally,the adaptive switch queue selection mechanism is introduced to solve the aggregation flow conflict problem effectively,queue resources are properly allocated,and the gate control list(GCL)of each frame in the queue is obtained.Experimental results show that compared with the traditional constraint model,the schedulability of the model with an adaptive switch queue selection mechanism increases by 33.0%,and the maximum end-to-end delay and network jitter decrease by 19.1%and 18.6%on average respectively.It can provide theoretical support and application reference for the real-time performance optimization of TCN based on TSN.
基金supported by the China Scholarship Council’s High-Level University Scholarship Program for Sponsored Graduate Students。
文摘Ⅰ.INTRODUCTION There are increasing concerns over data privacy,with information and communication technology proceeding at a rapid pace and posing intrusive challenges.Recognition of minors'vulnerability and transformation in their rights'protection occurred not far from where we stand at present.Such a combination breeds a new subject of exploring minors'personal data protection,among which the consent mechanism is highlighted.
基金supported by the National Natural Science Foundation of China(Grants Nos.U1605251,61727809 and 91546110)the Youth Innovation Promotion Association of CAS(2014299)Special Program for Applied Research on Super Computation of the NSFCGuangdong Joint Fund(the second phase).
文摘The propagation of information in online social networks plays a critical role in modern life,and thus has been studied broadly.Researchers have proposed a series of propagation models,generally,which use a single transition probability or consider factors such as content and time to describe the way how a user activates her/his neighbors.However,the research on the mechanism how social ties between users play roles in propagation process is still limited.Specifically,comprehensive summary of factors which affect user’s decision whether to share neighbor’s content was lacked in existing works,so that the existing models failed to clearly describe the process a user be activated by a neighbor.To this end,in this paper,we analyze the close correspondence between social tie in propagation process and communication channel,thus we propose to exploit the communication channel to describe the information propagation process between users,and design a social tie channel(STC)model.The model can naturally incorporate many factors affecting the information propagation through edges such as content topic and user preference,and thus can effectively capture the user behavior and relationship characteristics which indicate the property of a social tie.Extensive experiments conducted on two real-world datasets demonstrate the effectiveness of our model on content sharing prediction between users.
基金Supported by the National Natural Science Foundation of China(52074345)CNPC Research and Technology Development Project(2021ZG12).
文摘To study the fluid dynamic response mechanism under the working condition of water injection well borehole,based on the microelement analysis of fluid mechanics and the classical theory of hydrodynamics,a fluid microelement pressure-flow rate relationship model is built to derive and solve the dynamic distribution of fluid pressure and flow rate in the space of well borehole.Combined with the production data of a typical deviated well in China,numerical simulations and analyses are carried out to analyze the dynamic distribution of wellbore pressure at different injection pressures and injection volumes,the delayed and attenuated characteristics of fluid transmission in tube,and the dynamic distribution of wellbore pressure amplitude under the fluctuation of wellhead pressure.The pressure loss along the wellbore has nothing to do with the absolute pressure,and the design of the coding and decoding scheme for wave code communication doesn’t need to consider the absolute pressure during injecting.When the injection pressure is constant,the higher the injection flow rate at the wellhead,the larger the pressure loss along the wellbore.The fluid wave signal delay amplitude mainly depends on the length of the wellbore.The smaller the tubing diameter,the larger the fluid wave signal attenuation amplitude.The higher the target wave code amplitude(differential pressure identification root mean square)generated at the same well depth,the greater the wellhead pressure wave amplitude required to overcome the wellbore pressure loss.
文摘Against the backdrop of in-depth globalization and the rise of cultural mutual learning,the international communication of China’s Intangible Cultural Heritage(ICH)has become a key vehicle for enhancing China’s cultural soft power and engaging in global cultural dialogue.However,in cross-cultural contexts,this communication faces structural dilemmas at multiple levels.From a cross-cultural perspective,this study proposes targeted solutions to address these dilemmas.The ultimate goal is to promote the transformation of China’s ICH international communication from“symbolic display”to“meaning sharing”and from“cultural output”to“value resonance”,thereby enhancing the effectiveness of cross-cultural communication and advancing the global recognition of China’s ICH.
基金supported by the National Natural Science Foundation of China,No.82071278(to PY)Outstanding Young Medical Talents Project of Changhai Hospital,No.2021JCSQ03(to PY)+1 种基金Shanghai Sailing Program,No.20YF1448000(to XZ)Medical Health Science and Technology Project of Zhoushan City,No.2022JRC01(to HL).
文摘Astrocytes are the most abundant glial cells in the central nervous system;they participate in crucial biological processes,maintain brain structure,and regulate nervous system function.Exosomes are cell-derived extracellular vesicles containing various bioactive molecules including proteins,peptides,nucleotides,and lipids secreted from their cellular sources.Increasing evidence shows that exosomes participate in a communication network in the nervous system,in which astrocyte-derived exosomes play important roles.In this review,we have summarized the effects of exosomes targeting astrocytes and the astrocyte-derived exosomes targeting other cell types in the central nervous system.We also discuss the potential research directions of the exosome-based communication network in the nervous system.The exosome-based intercellular communication focused on astrocytes is of great significance to the biological and/or pathological processes in different conditions in the brain.New strategies may be developed for the diagnosis and treatment of neurological disorders by focusing on astrocytes as the central cells and utilizing exosomes as communication mediators.
基金This work was supported by the Beijing Natural Science Foundation(L202003).
文摘Satellite communication systems are facing serious electromagnetic interference,and interference signal recognition is a crucial foundation for targeted anti-interference.In this paper,we propose a novel interference recognition algorithm called HDCGD-CBAM,which adopts the time-frequency images(TFIs)of signals to effectively extract the temporal and spectral characteristics.In the proposed method,we improve the Convolutional Long Short-Term Memory Deep Neural Network(CLDNN)in two ways.First,the simpler Gate Recurrent Unit(GRU)is used instead of the Long Short-Term Memory(LSTM),reducing model parameters while maintaining the recognition accuracy.Second,we replace convolutional layers with hybrid dilated convolution(HDC)to expand the receptive field of feature maps,which captures the correlation of time-frequency data on a larger spatial scale.Additionally,Convolutional Block Attention Module(CBAM)is introduced before and after the HDC layers to strengthen the extraction of critical features and improve the recognition performance.The experiment results show that the HDCGD-CBAM model significantly outper-forms existing methods in terms of recognition accuracy and complexity.When Jamming-to-Signal Ratio(JSR)varies from-30dB to 10dB,it achieves an average accuracy of 78.7%and outperforms the CLDNN by 7.29%while reducing the Floating Point Operations(FLOPs)by 79.8%to 114.75M.Moreover,the proposed model has fewer parameters with 301k compared to several state-of-the-art methods.
基金supported in part by the National Natural Science Foundation of China(51939001,61976033,62273072)the Natural Science Foundation of Sichuan Province (2022NSFSC0903)。
文摘This paper investigates the consensus control of multi-agent systems(MASs) with constrained input using the dynamic event-triggered mechanism(ETM).Consider the MASs with small-scale networks where a centralized dynamic ETM with global information of the MASs is first designed.Then,a distributed dynamic ETM which only uses local information is developed for the MASs with large-scale networks.It is shown that the semi-global consensus of the MASs can be achieved by the designed bounded control protocol where the Zeno phenomenon is eliminated by a designable minimum inter-event time.In addition,it is easier to find a trade-off between the convergence rate and the minimum inter-event time by an adjustable parameter.Furthermore,the results are extended to regional consensus of the MASs with the bounded control protocol.Numerical simulations show the effectiveness of the proposed approach.
文摘Artificial Intelligence (AI) is transforming organizational dynamics, and revolutionizing corporate leadership practices. This research paper delves into the question of how AI influences corporate leadership, examining both its advantages and disadvantages. Positive impacts of AI are evident in communication, feedback systems, tracking mechanisms, and decision-making processes within organizations. AI-powered communication tools, as exemplified by Slack, facilitate seamless collaboration, transcending geographical barriers. Feedback systems, like Adobe’s Performance Management System, employ AI algorithms to provide personalized development opportunities, enhancing employee growth. AI-based tracking systems optimize resource allocation, as exemplified by studies like “AI-Based Tracking Systems: Enhancing Efficiency and Accountability.” Additionally, AI-powered decision support, demonstrated during the COVID-19 pandemic, showcases the capability to navigate complex challenges and maintain resilience. However, AI adoption poses challenges in human resources, potentially leading to job displacement and necessitating upskilling efforts. Managing AI errors becomes crucial, as illustrated by instances like Amazon’s biased recruiting tool. Data privacy concerns also arise, emphasizing the need for robust security measures. The proposed solution suggests leveraging Local Machine Learning Models (LLMs) to address data privacy issues. Approaches such as federated learning, on-device learning, differential privacy, and homomorphic encryption offer promising strategies. By exploring the evolving dynamics of AI and leadership, this research advocates for responsible AI adoption and proposes LLMs as a potential solution, fostering a balanced integration of AI benefits while mitigating associated risks in corporate settings.
基金supported financially by National Natural Science Foundation of China(NSFC12372312,11872129)Projects of“Jiangsu Specially-appointed Professor”(M.O.)National Natural Science Foundation of China(11902051(B.B.),12272063(L.D.)).
文摘The progression of tumors is heavily influenced by mechanical properties of their microenvironment.In this work,we applied micropatterned models with varying distances and shapes to investigate the differences between metastatic MDA-MB-231 and non-metastatic MCF-7 breast cancer cells in reconfiguring extracellular matrix to promote cell migration induced by cell mechanics.Both cancer cells were able to rearrange type I collagen(COL)to form fibre threads,in which MDA-MB-231 consistently migrated more rapidly than MCF-7,ranging from geometrical square arrays with different spacings to complex polygonal models.MDA-MB-231 displayed higher capability of reorganizing fibre bundles at longer distance(800μm).Further looking for differences in cell molecular mechanisms,siRNA knockdown inhibiting either integrinβ1 or Piezo1 decreased fibre assembly and reduced the difference in COL remodeling and migration between two cancer cells.MDA-MB-231 showed inhibited migration with integrin knockdown,whereas scattering migration with Piezo1 knockdown,indicating cells losing directional mechanosensation.After inhibiting junctional E-cadherin with siRNA,MCF-7 cells migrated faster,resulting in reduced difference in comparison to MDA-MB-231 that didn't express E-cadherin.In summary,this work has explored the biomechanical differences between metastatic and non-metastatic breast cancer cells regarding COL fibre matrix remodeling and cell movements.The significant differences in E-cadherin expression in the two breast cancer cells had an effect on cell migrations.The results of this study provide research approaches for evaluating therapeutic effort on breast cancer.
