Optical neural networks have significant advantages in terms of power consumption,parallelism,and high computing speed,which has intrigued extensive attention in both academic and engineering communities.It has been c...Optical neural networks have significant advantages in terms of power consumption,parallelism,and high computing speed,which has intrigued extensive attention in both academic and engineering communities.It has been considered as one of the powerful tools in promoting the fields of imaging processing and object recognition.However,the existing optical system architecture cannot be reconstructed to the realization of multi-functional artificial intelligence systems simultaneously.To push the development of this issue,we propose the pluggable diffractive neural networks(P-DNN),a general paradigm resorting to the cascaded metasurfaces,which can be applied to recognize various tasks by switching internal plug-ins.As the proof-of-principle,the recognition functions of six types of handwritten digits and six types of fashions are numerical simulated and experimental demonstrated at near-infrared regimes.Encouragingly,the proposed paradigm not only improves the flexibility of the optical neural networks but paves the new route for achieving high-speed,low-power and versatile artificial intelligence systems.展开更多
Medical procedures are inherently invasive and carry the risk of inducing pain to the mind and body.Recently,efforts have been made to alleviate the discomfort associated with invasive medical procedures through the u...Medical procedures are inherently invasive and carry the risk of inducing pain to the mind and body.Recently,efforts have been made to alleviate the discomfort associated with invasive medical procedures through the use of virtual reality(VR)technology.VR has been demonstrated to be an effective treatment for pain associated with medical procedures,as well as for chronic pain conditions for which no effective treatment has been established.The precise mechanism by which the diversion from reality facilitated by VR contributes to the diminution of pain and anxiety has yet to be elucidated.However,the provision of positive images through VR-based visual stimulation may enhance the functionality of brain networks.The salience network is diminished,while the default mode network is enhanced.Additionally,the medial prefrontal cortex may establish a stronger connection with the default mode network,which could result in a reduction of pain and anxiety.Further research into the potential of VR technology to alleviate pain could lead to a reduction in the number of individuals who overdose on painkillers and contribute to positive change in the medical field.展开更多
BACKGROUND Mitochondrial genes are involved in tumor metabolism in ovarian cancer(OC)and affect immune cell infiltration and treatment responses.AIM To predict prognosis and immunotherapy response in patients diagnose...BACKGROUND Mitochondrial genes are involved in tumor metabolism in ovarian cancer(OC)and affect immune cell infiltration and treatment responses.AIM To predict prognosis and immunotherapy response in patients diagnosed with OC using mitochondrial genes and neural networks.METHODS Prognosis,immunotherapy efficacy,and next-generation sequencing data of patients with OC were downloaded from The Cancer Genome Atlas and Gene Expression Omnibus.Mitochondrial genes were sourced from the MitoCarta3.0 database.The discovery cohort for model construction was created from 70% of the patients,whereas the remaining 30% constituted the validation cohort.Using the expression of mitochondrial genes as the predictor variable and based on neural network algorithm,the overall survival time and immunotherapy efficacy(complete or partial response)of patients were predicted.RESULTS In total,375 patients with OC were included to construct the prognostic model,and 26 patients were included to construct the immune efficacy model.The average area under the receiver operating characteristic curve of the prognostic model was 0.7268[95% confidence interval(CI):0.7258-0.7278]in the discovery cohort and 0.6475(95%CI:0.6466-0.6484)in the validation cohort.The average area under the receiver operating characteristic curve of the immunotherapy efficacy model was 0.9444(95%CI:0.8333-1.0000)in the discovery cohort and 0.9167(95%CI:0.6667-1.0000)in the validation cohort.CONCLUSION The application of mitochondrial genes and neural networks has the potential to predict prognosis and immunotherapy response in patients with OC,providing valuable insights into personalized treatment strategies.展开更多
Wireless sensor network (WSN) of active sensors suffers from serious inter-sensor interference (ISI) and imposes new design and implementation challenges. In this paper, based on the ultrasonic sensor network, two tim...Wireless sensor network (WSN) of active sensors suffers from serious inter-sensor interference (ISI) and imposes new design and implementation challenges. In this paper, based on the ultrasonic sensor network, two time-division based distributed sensor scheduling schemes are proposed to deal with ISI by scheduling sensors periodically and adaptively respectively. Extended Kalman filter (EKF) is used as the tracking algorithm in distributed manner. Simulation results show that the adaptive sensor scheduling scheme can achieve superior tracking accuracy with faster tracking convergence speed.展开更多
Active Queue Management (AQM) is an active research area in the Internet community. Random Early Detection (RED) is a typical AQM algorithm, but it is known that it is difficult to configure its parameters and its ave...Active Queue Management (AQM) is an active research area in the Internet community. Random Early Detection (RED) is a typical AQM algorithm, but it is known that it is difficult to configure its parameters and its average queue length is closely related to the load level. This paper proposes an effective fuzzy congestion control algorithm based on fuzzy logic which uses the pre- dominance of fuzzy logic to deal with uncertain events. The main advantage of this new congestion control algorithm is that it discards the packet dropping mechanism of RED, and calculates packet loss according to a preconfigured fuzzy logic by using the queue length and the buffer usage ratio. Theo- retical analysis and Network Simulator (NS) simulation results show that the proposed algorithm achieves more throughput and more stable queue length than traditional schemes. It really improves a router's ability in network congestion control in IP network.展开更多
Optical deep learning based on diffractive optical elements offers unique advantages for parallel processing,computational speed,and power efficiency.One landmark method is the diffractive deep neural network(D^(2) NN...Optical deep learning based on diffractive optical elements offers unique advantages for parallel processing,computational speed,and power efficiency.One landmark method is the diffractive deep neural network(D^(2) NN)based on three-dimensional printing technology operated in the terahertz spectral range.Since the terahertz bandwidth involves limited interparticle coupling and material losses,this paper extends D^(2) NN to visible wavelengths.A general theory including a revised formula is proposed to solve any contradictions between wavelength,neuron size,and fabrication limitations.A novel visible light D^(2) NN classifier is used to recognize unchanged targets(handwritten digits ranging from 0 to 9)and targets that have been changed(i.e.,targets that have been covered or altered)at a visible wavelength of 632.8 nm.The obtained experimental classification accuracy(84%)and numerical classification accuracy(91.57%)quantify the match between the theoretical design and fabricated system performance.The presented framework can be used to apply a D^(2) NN to various practical applications and design other new applications.展开更多
In this paper, the control method for fixed offshore platforms using semi-active tuned liquid column damper (TLCD) is presented. The equation of motion for the platform-TLCD control system is given and the semi-active...In this paper, the control method for fixed offshore platforms using semi-active tuned liquid column damper (TLCD) is presented. The equation of motion for the platform-TLCD control system is given and the semi-active control strategy is established. A back propagation artificial neural network (ANN) is used to adjust the orifice opening of TLCD because of the nonlinear motion of liquid in TLCD. The effectiveness of the control method is verified by numerical examples.展开更多
In this paper, we propose a new mechanism called explicit rate notification(ERN) to be used in end-to-end communications. The ERN scheme encodes in the header of transmission control protocol(TCP) packets information ...In this paper, we propose a new mechanism called explicit rate notification(ERN) to be used in end-to-end communications. The ERN scheme encodes in the header of transmission control protocol(TCP) packets information about the sending rate and the round trip time(RTT) of the flows. This new available information to the intermediate nodes(routers) is used to improve fairness, increase utilization, decrease the number of drops, and minimize queueing delays. Thus, it induces a better management of the queue. A comparison of our scheme with preexistent schemes, like the explicit congestion notification scheme, shows the effectiveness of the proposed mechanism.展开更多
The emergence of self-driving technologies implies that a future vehicle will likely become an entertainment center that demands personalized multimedia contents with very high quality. The surge of vehicular content ...The emergence of self-driving technologies implies that a future vehicle will likely become an entertainment center that demands personalized multimedia contents with very high quality. The surge of vehicular content demand brings significant challenges for the fifth generation(5G) cellular communication network. To cope with the challenge of massive content delivery, previous studies suggested that the 5G mobile edge network should be designed to integrate communication, computing, and cache(3C) resources to enable advanced functionalities such as proactive content delivery and in-network caching. However, the fundamental benefits achievable by computing and caching in mobile communications networks are not yet properly understood. This paper proposes a novel theoretical framework to characterize the tradeoff among computing, cache, and communication resources required by the mobile edge network to fulfill the task of content delivery. Analytical and numerical results are obtained to characterize the 3C resource tradeoff curve. These results reveal key insights into the fundamental benefits of computing and caching in vehicular mobile content delivery networks.展开更多
Active networks is primarily a Defense Advanced Research Projects Agency(DARPA)-funded project focusing on the research of mechanisms, applications, and operating systems to develop a reconfigurable network infrastruc...Active networks is primarily a Defense Advanced Research Projects Agency(DARPA)-funded project focusing on the research of mechanisms, applications, and operating systems to develop a reconfigurable network infrastructure. This letter proposes an Secure Active Tracing System (SATS) to implementing security for active networking in Internet. Unlike currently existing schemes, SATS reduces the computational overloads by executing the filtering operation on selected packet streams only when needed.展开更多
This paper provides a deep evaluation of the energy consumption of routing protocols. The evaluation is done along with other metrics such as throughput and packet delivery ratio (PDR). We introduce two more metrics t...This paper provides a deep evaluation of the energy consumption of routing protocols. The evaluation is done along with other metrics such as throughput and packet delivery ratio (PDR). We introduce two more metrics to capture the efficiency of the energy consumption: e-throughput and e-PDR. Both are ratios in relation to the energy. We consider the three low layers of the stack. Three types of routing protocols are used: proactive, reactive, and hybrid. At the MAC and PHY layer, three radio types are considered: 802.11a/b/g. Finally, the number of nodes is varying in random topologies, with nodes being static or mobile. Simulations are conducted using NS3. The parameters of a real network interface card are used. From the results in mobile position scenarios, no protocol is outperforming the others;even if OLSR has the lowest energy consumption, most of the time. However, in constant position scenarios, AODV consumed a lower energy, apart from the scenarios using the 802.11a standard where HWMP energy consumption is the lowest. Regarding the energy efficiency, AODV protocols provided the best e-throughput and OLSR the best e-PDR in overall configurations. A framework for selecting energy-efficient routing protocol depending on network characteristics is proposed at the end.展开更多
A previous proactive RSA scheme for large-scale ad hoc network has been shown to be faulty. In this paper, we present a new proactive RSA scheme for ad hoc networks, which includes four protocols: the initial key dis...A previous proactive RSA scheme for large-scale ad hoc network has been shown to be faulty. In this paper, we present a new proactive RSA scheme for ad hoc networks, which includes four protocols: the initial key distribution protocol, the share refreshing protocol, the share distribution protocol, and the signature generation protocol. This scheme has two advantages: the building blocks are secure, and the system is efficient.展开更多
In this paper, we propose the dynamically-evolving active overlay network (DEAON), which is an efficient, scalable yet simple protocol to facilitate applications of decentralized information retrieval in P2P network...In this paper, we propose the dynamically-evolving active overlay network (DEAON), which is an efficient, scalable yet simple protocol to facilitate applications of decentralized information retrieval in P2P networks. DEAON consists of three novel components : a Desirable Topology Construction and Adaptation algorithm to guide the evolution of the overlay topology towards a small-world-like graph; a Semantic-based Neighbor Selection scheme to conduct an online neighbor ranking; a Topology-aware Intelligent Search mechanism to forward incoming queries to deliberately selected neighbors. We deploy and compare DEAON with other several existing distributed search techniques over static and dynamic environments. The results indicate that DEAON outperforms its competitors by achieving higher recall rate while using much less network resources, in both of the above environments.展开更多
The non-linear relationships between the contents of ginsenoside Rg 1, Rb 1, Rd and Panax notoginseng saponins(PNS) in Panax notoginseng root herb and the near infrared(NIR) diffuse reflectance spectra of the herb wer...The non-linear relationships between the contents of ginsenoside Rg 1, Rb 1, Rd and Panax notoginseng saponins(PNS) in Panax notoginseng root herb and the near infrared(NIR) diffuse reflectance spectra of the herb were established by means of artificial neural networks(ANNs). Four three-layered perception feed-forward networks were trained with an error back-propagation algorithm. The significant principal components of the NIR spectral data matrix were utilized as the input of the networks. The networks architecture and parameters were selected so as to offer less prediction errors. Relative prediction errors for Rg 1, Rb 1, Rd and PNS obtained with the optimum ANN models were 8.99%, 6.54%, 8.29%, and 5.17%, respectively, which were superior to those obtained with PLSR methods. It is verified that ANN is a suitable approach to model this complex non-linearity. The developed method is fast, non-destructive and accurate and it provides a new efficient approach for determining the active components in the complex system of natural herbs.展开更多
An efficient method for the optimization of linear networks is presented.Thecomputation cost in circuit optimization mainly depends on the simulation of network;in general,the simulation of a linear network needs to s...An efficient method for the optimization of linear networks is presented.Thecomputation cost in circuit optimization mainly depends on the simulation of network;in general,the simulation of a linear network needs to solve a high dimension linear algebra equation.Animportant characteristic in circuit optimization is that the number of independently tunableparameters is small.In terms of the property of linear networks,the circuit is described by amultiport network in the presented method,and the hybrid matrix is established.The dimensionof the equation to be solved is the same as the number of optimization parameters in objectivefunction evaluations,which provides a fast simulation tool for optimization.展开更多
目的以入血成分为研究对象,基于网络药理学探究衢枳壳对糖尿病起效的物质基础及作用机制。方法采用高效液相色谱串联四极杆-静电场轨道阱高分辨质谱(high-performance liquid chromatography tandem quadrupole-electrostatic field orb...目的以入血成分为研究对象,基于网络药理学探究衢枳壳对糖尿病起效的物质基础及作用机制。方法采用高效液相色谱串联四极杆-静电场轨道阱高分辨质谱(high-performance liquid chromatography tandem quadrupole-electrostatic field orbitrap high resolution mass spectrometry,HPLC-Q-Exactive Orbitrap MS/MS)对衢枳壳入血成分进行鉴定,在此基础上通过Swiss Target Prediction与SuperPred数据库预测入血成分作用靶点,同时在OMIM,GeneCards等数据库获取糖尿病靶点。采用Cytoscape 3.9.1绘制中药衢枳壳“活性成分-靶点-疾病”网络关系图,利用String数据分析平台进行蛋白互作(protein-protein interaction,PPI)网络分析,筛选关键靶点。通过DAVID数据库对关键靶点进行基因本体功能(gene ontology,GO)和京都基因与基因组百科全书(kyoto encyclopedia of genes and genomes,KEGG)通路富集分析。应用Autodock 1.5.7软件进行分子对接验证。结果共鉴定衢枳壳入血成分20个,筛选出潜在靶点170个,核心靶点32个。GO功能富集和KEGG信号通路分析结果显示缺氧诱导因子(hypoxia-inducible factor,HIF)-1信号通路、晚期糖基化终末产物(advanced glycation end products,AGE)-晚期糖基化终产物受体(receptor for advanced glycation end products,RAGE)信号通路、表皮生长因子(epidermal growth factor receptor,EGFR)信号通路、癌症蛋白聚糖通路等为衢枳壳降糖的关键通路,丝氨酸/苏氨酸蛋白激酶(RAC serine/threonine-protein kinase,AKT)1、白蛋白(albumin,ALB)、细胞肿瘤抗原p53(cellular tumor antigenp 53,TP53)、肿瘤坏死因子(tumor necrosis factor,TNF)、EGFR为其中关键靶点,且衢枳壳中5个活性成分与核心靶点经分子对接后的结合活性较好。结论衢枳壳中的芦丁、新橙皮苷、橙皮苷、芸香柚皮苷、川陈皮素等可能为衢枳壳降糖的物质基础,可能是通过调控HIF-1、AGE-RAGE、EGFR等信号通路及AKT1、ALB、TP53等核心基因发挥降糖作用。展开更多
After decades of theoretical studies,the rich phase states of active matter and cluster kinetic processes are still of research interest.How to efficiently calculate the dynamical processes under their complex conditi...After decades of theoretical studies,the rich phase states of active matter and cluster kinetic processes are still of research interest.How to efficiently calculate the dynamical processes under their complex conditions becomes an open problem.Recently,machine learning methods have been proposed to predict the degree of coherence of active matter systems.In this way,the phase transition process of the system is quantified and studied.In this paper,we use graph network as a powerful model to determine the evolution of active matter with variable individual velocities solely based on the initial position and state of the particles.The graph network accurately predicts the order parameters of the system in different scale models with different individual velocities,noise and density to effectively evaluate the effect of diverse condition.Compared with the classical physical deduction method,we demonstrate that graph network prediction is excellent,which could save significantly computing resources and time.In addition to active matter,our method can be applied widely to other large-scale physical systems.展开更多
Author present the interplay between different neuron types in the spontaneous electrical activity of low density cortical in vitro networks grown on MEA (multielectrode arrays) of glass neurochips. In 10% of the ne...Author present the interplay between different neuron types in the spontaneous electrical activity of low density cortical in vitro networks grown on MEA (multielectrode arrays) of glass neurochips. In 10% of the networks, the continuously spiking activity of some neurons was inhibited by synchronous bursts or superbursts of the majority of the other neurons. Immunohistochemical staining subsequent to MEA recordings suggest that the synchronously bursting neurons are parvalbumin-positive interneurons with abundant axonal ramifications. Blocking chemical synaptic transmission by Ca2+-free medium revealed that the curbed spiking neurons are intrinsically active. It is assumed that these neurons are pyramidal cells which may be inhibited by groups of synchronously bursting interneurons. It is propose that the observed burst-induced inhibition is an important principle in the temporal organization of neuronal activity as well as in the restriction of excitation, and thus essential for information processing in the cerebral cortex.展开更多
With the expansion of distributed generation systems and demand response programs, the need to fully utilize distribution system capacity has increased. In addition, the potential bidirectional flow of power on distri...With the expansion of distributed generation systems and demand response programs, the need to fully utilize distribution system capacity has increased. In addition, the potential bidirectional flow of power on distribution networks demands voltage visibility and control at all voltage levels. Distribution system state estimations, however, have traditionally been less prioritized due to the lack of enough measurement points while being the major role player in knowing the real-time system states of active distribution networks. The advent of smart meters at LV loads, on the other hand, is giving relief to this shortcoming. This study explores the potential of bottom up load flow analysis based on customer level Automatic Meter Reading (AMRs) to compute short time forecasts of demands and distribution network system states. A state estimation frame-work, which makes use of available AMR data, is proposed and discussed.展开更多
基金The authors acknowledge the funding provided by the National Key R&D Program of China(2021YFA1401200)Beijing Outstanding Young Scientist Program(BJJWZYJH01201910007022)+2 种基金National Natural Science Foundation of China(No.U21A20140,No.92050117,No.62005017)programBeijing Municipal Science&Technology Commission,Administrative Commission of Zhongguancun Science Park(No.Z211100004821009)This work was supported by the Synergetic Extreme Condition User Facility(SECUF).
文摘Optical neural networks have significant advantages in terms of power consumption,parallelism,and high computing speed,which has intrigued extensive attention in both academic and engineering communities.It has been considered as one of the powerful tools in promoting the fields of imaging processing and object recognition.However,the existing optical system architecture cannot be reconstructed to the realization of multi-functional artificial intelligence systems simultaneously.To push the development of this issue,we propose the pluggable diffractive neural networks(P-DNN),a general paradigm resorting to the cascaded metasurfaces,which can be applied to recognize various tasks by switching internal plug-ins.As the proof-of-principle,the recognition functions of six types of handwritten digits and six types of fashions are numerical simulated and experimental demonstrated at near-infrared regimes.Encouragingly,the proposed paradigm not only improves the flexibility of the optical neural networks but paves the new route for achieving high-speed,low-power and versatile artificial intelligence systems.
文摘Medical procedures are inherently invasive and carry the risk of inducing pain to the mind and body.Recently,efforts have been made to alleviate the discomfort associated with invasive medical procedures through the use of virtual reality(VR)technology.VR has been demonstrated to be an effective treatment for pain associated with medical procedures,as well as for chronic pain conditions for which no effective treatment has been established.The precise mechanism by which the diversion from reality facilitated by VR contributes to the diminution of pain and anxiety has yet to be elucidated.However,the provision of positive images through VR-based visual stimulation may enhance the functionality of brain networks.The salience network is diminished,while the default mode network is enhanced.Additionally,the medial prefrontal cortex may establish a stronger connection with the default mode network,which could result in a reduction of pain and anxiety.Further research into the potential of VR technology to alleviate pain could lead to a reduction in the number of individuals who overdose on painkillers and contribute to positive change in the medical field.
基金Supported by National Key Technology Research and Developmental Program of China,No.2022YFC2704400 and No.2022YFC2704405.
文摘BACKGROUND Mitochondrial genes are involved in tumor metabolism in ovarian cancer(OC)and affect immune cell infiltration and treatment responses.AIM To predict prognosis and immunotherapy response in patients diagnosed with OC using mitochondrial genes and neural networks.METHODS Prognosis,immunotherapy efficacy,and next-generation sequencing data of patients with OC were downloaded from The Cancer Genome Atlas and Gene Expression Omnibus.Mitochondrial genes were sourced from the MitoCarta3.0 database.The discovery cohort for model construction was created from 70% of the patients,whereas the remaining 30% constituted the validation cohort.Using the expression of mitochondrial genes as the predictor variable and based on neural network algorithm,the overall survival time and immunotherapy efficacy(complete or partial response)of patients were predicted.RESULTS In total,375 patients with OC were included to construct the prognostic model,and 26 patients were included to construct the immune efficacy model.The average area under the receiver operating characteristic curve of the prognostic model was 0.7268[95% confidence interval(CI):0.7258-0.7278]in the discovery cohort and 0.6475(95%CI:0.6466-0.6484)in the validation cohort.The average area under the receiver operating characteristic curve of the immunotherapy efficacy model was 0.9444(95%CI:0.8333-1.0000)in the discovery cohort and 0.9167(95%CI:0.6667-1.0000)in the validation cohort.CONCLUSION The application of mitochondrial genes and neural networks has the potential to predict prognosis and immunotherapy response in patients with OC,providing valuable insights into personalized treatment strategies.
基金Supported by Science & Engineering Research Council of Singnpore (0521010037)
文摘Wireless sensor network (WSN) of active sensors suffers from serious inter-sensor interference (ISI) and imposes new design and implementation challenges. In this paper, based on the ultrasonic sensor network, two time-division based distributed sensor scheduling schemes are proposed to deal with ISI by scheduling sensors periodically and adaptively respectively. Extended Kalman filter (EKF) is used as the tracking algorithm in distributed manner. Simulation results show that the adaptive sensor scheduling scheme can achieve superior tracking accuracy with faster tracking convergence speed.
基金Supported by the National High Technology Research and Development of China (863 Program) (No.2003AA121560)the High Technology Research and Development Program of Jiangsu Province (No.BEG2003001).
文摘Active Queue Management (AQM) is an active research area in the Internet community. Random Early Detection (RED) is a typical AQM algorithm, but it is known that it is difficult to configure its parameters and its average queue length is closely related to the load level. This paper proposes an effective fuzzy congestion control algorithm based on fuzzy logic which uses the pre- dominance of fuzzy logic to deal with uncertain events. The main advantage of this new congestion control algorithm is that it discards the packet dropping mechanism of RED, and calculates packet loss according to a preconfigured fuzzy logic by using the queue length and the buffer usage ratio. Theo- retical analysis and Network Simulator (NS) simulation results show that the proposed algorithm achieves more throughput and more stable queue length than traditional schemes. It really improves a router's ability in network congestion control in IP network.
基金This research was supported in part by National Natural Science Foundation of China(61675056 and 61875048).
文摘Optical deep learning based on diffractive optical elements offers unique advantages for parallel processing,computational speed,and power efficiency.One landmark method is the diffractive deep neural network(D^(2) NN)based on three-dimensional printing technology operated in the terahertz spectral range.Since the terahertz bandwidth involves limited interparticle coupling and material losses,this paper extends D^(2) NN to visible wavelengths.A general theory including a revised formula is proposed to solve any contradictions between wavelength,neuron size,and fabrication limitations.A novel visible light D^(2) NN classifier is used to recognize unchanged targets(handwritten digits ranging from 0 to 9)and targets that have been changed(i.e.,targets that have been covered or altered)at a visible wavelength of 632.8 nm.The obtained experimental classification accuracy(84%)and numerical classification accuracy(91.57%)quantify the match between the theoretical design and fabricated system performance.The presented framework can be used to apply a D^(2) NN to various practical applications and design other new applications.
文摘In this paper, the control method for fixed offshore platforms using semi-active tuned liquid column damper (TLCD) is presented. The equation of motion for the platform-TLCD control system is given and the semi-active control strategy is established. A back propagation artificial neural network (ANN) is used to adjust the orifice opening of TLCD because of the nonlinear motion of liquid in TLCD. The effectiveness of the control method is verified by numerical examples.
文摘In this paper, we propose a new mechanism called explicit rate notification(ERN) to be used in end-to-end communications. The ERN scheme encodes in the header of transmission control protocol(TCP) packets information about the sending rate and the round trip time(RTT) of the flows. This new available information to the intermediate nodes(routers) is used to improve fairness, increase utilization, decrease the number of drops, and minimize queueing delays. Thus, it induces a better management of the queue. A comparison of our scheme with preexistent schemes, like the explicit congestion notification scheme, shows the effectiveness of the proposed mechanism.
基金the support from the Natural Science Foundation of China (Grant No.61571378)
文摘The emergence of self-driving technologies implies that a future vehicle will likely become an entertainment center that demands personalized multimedia contents with very high quality. The surge of vehicular content demand brings significant challenges for the fifth generation(5G) cellular communication network. To cope with the challenge of massive content delivery, previous studies suggested that the 5G mobile edge network should be designed to integrate communication, computing, and cache(3C) resources to enable advanced functionalities such as proactive content delivery and in-network caching. However, the fundamental benefits achievable by computing and caching in mobile communications networks are not yet properly understood. This paper proposes a novel theoretical framework to characterize the tradeoff among computing, cache, and communication resources required by the mobile edge network to fulfill the task of content delivery. Analytical and numerical results are obtained to characterize the 3C resource tradeoff curve. These results reveal key insights into the fundamental benefits of computing and caching in vehicular mobile content delivery networks.
文摘Active networks is primarily a Defense Advanced Research Projects Agency(DARPA)-funded project focusing on the research of mechanisms, applications, and operating systems to develop a reconfigurable network infrastructure. This letter proposes an Secure Active Tracing System (SATS) to implementing security for active networking in Internet. Unlike currently existing schemes, SATS reduces the computational overloads by executing the filtering operation on selected packet streams only when needed.
文摘This paper provides a deep evaluation of the energy consumption of routing protocols. The evaluation is done along with other metrics such as throughput and packet delivery ratio (PDR). We introduce two more metrics to capture the efficiency of the energy consumption: e-throughput and e-PDR. Both are ratios in relation to the energy. We consider the three low layers of the stack. Three types of routing protocols are used: proactive, reactive, and hybrid. At the MAC and PHY layer, three radio types are considered: 802.11a/b/g. Finally, the number of nodes is varying in random topologies, with nodes being static or mobile. Simulations are conducted using NS3. The parameters of a real network interface card are used. From the results in mobile position scenarios, no protocol is outperforming the others;even if OLSR has the lowest energy consumption, most of the time. However, in constant position scenarios, AODV consumed a lower energy, apart from the scenarios using the 802.11a standard where HWMP energy consumption is the lowest. Regarding the energy efficiency, AODV protocols provided the best e-throughput and OLSR the best e-PDR in overall configurations. A framework for selecting energy-efficient routing protocol depending on network characteristics is proposed at the end.
基金Project supported by the National Natural Science Foundation of China(Grant No.60273049)
文摘A previous proactive RSA scheme for large-scale ad hoc network has been shown to be faulty. In this paper, we present a new proactive RSA scheme for ad hoc networks, which includes four protocols: the initial key distribution protocol, the share refreshing protocol, the share distribution protocol, and the signature generation protocol. This scheme has two advantages: the building blocks are secure, and the system is efficient.
文摘In this paper, we propose the dynamically-evolving active overlay network (DEAON), which is an efficient, scalable yet simple protocol to facilitate applications of decentralized information retrieval in P2P networks. DEAON consists of three novel components : a Desirable Topology Construction and Adaptation algorithm to guide the evolution of the overlay topology towards a small-world-like graph; a Semantic-based Neighbor Selection scheme to conduct an online neighbor ranking; a Topology-aware Intelligent Search mechanism to forward incoming queries to deliberately selected neighbors. We deploy and compare DEAON with other several existing distributed search techniques over static and dynamic environments. The results indicate that DEAON outperforms its competitors by achieving higher recall rate while using much less network resources, in both of the above environments.
文摘The non-linear relationships between the contents of ginsenoside Rg 1, Rb 1, Rd and Panax notoginseng saponins(PNS) in Panax notoginseng root herb and the near infrared(NIR) diffuse reflectance spectra of the herb were established by means of artificial neural networks(ANNs). Four three-layered perception feed-forward networks were trained with an error back-propagation algorithm. The significant principal components of the NIR spectral data matrix were utilized as the input of the networks. The networks architecture and parameters were selected so as to offer less prediction errors. Relative prediction errors for Rg 1, Rb 1, Rd and PNS obtained with the optimum ANN models were 8.99%, 6.54%, 8.29%, and 5.17%, respectively, which were superior to those obtained with PLSR methods. It is verified that ANN is a suitable approach to model this complex non-linearity. The developed method is fast, non-destructive and accurate and it provides a new efficient approach for determining the active components in the complex system of natural herbs.
文摘An efficient method for the optimization of linear networks is presented.Thecomputation cost in circuit optimization mainly depends on the simulation of network;in general,the simulation of a linear network needs to solve a high dimension linear algebra equation.Animportant characteristic in circuit optimization is that the number of independently tunableparameters is small.In terms of the property of linear networks,the circuit is described by amultiport network in the presented method,and the hybrid matrix is established.The dimensionof the equation to be solved is the same as the number of optimization parameters in objectivefunction evaluations,which provides a fast simulation tool for optimization.
文摘目的以入血成分为研究对象,基于网络药理学探究衢枳壳对糖尿病起效的物质基础及作用机制。方法采用高效液相色谱串联四极杆-静电场轨道阱高分辨质谱(high-performance liquid chromatography tandem quadrupole-electrostatic field orbitrap high resolution mass spectrometry,HPLC-Q-Exactive Orbitrap MS/MS)对衢枳壳入血成分进行鉴定,在此基础上通过Swiss Target Prediction与SuperPred数据库预测入血成分作用靶点,同时在OMIM,GeneCards等数据库获取糖尿病靶点。采用Cytoscape 3.9.1绘制中药衢枳壳“活性成分-靶点-疾病”网络关系图,利用String数据分析平台进行蛋白互作(protein-protein interaction,PPI)网络分析,筛选关键靶点。通过DAVID数据库对关键靶点进行基因本体功能(gene ontology,GO)和京都基因与基因组百科全书(kyoto encyclopedia of genes and genomes,KEGG)通路富集分析。应用Autodock 1.5.7软件进行分子对接验证。结果共鉴定衢枳壳入血成分20个,筛选出潜在靶点170个,核心靶点32个。GO功能富集和KEGG信号通路分析结果显示缺氧诱导因子(hypoxia-inducible factor,HIF)-1信号通路、晚期糖基化终末产物(advanced glycation end products,AGE)-晚期糖基化终产物受体(receptor for advanced glycation end products,RAGE)信号通路、表皮生长因子(epidermal growth factor receptor,EGFR)信号通路、癌症蛋白聚糖通路等为衢枳壳降糖的关键通路,丝氨酸/苏氨酸蛋白激酶(RAC serine/threonine-protein kinase,AKT)1、白蛋白(albumin,ALB)、细胞肿瘤抗原p53(cellular tumor antigenp 53,TP53)、肿瘤坏死因子(tumor necrosis factor,TNF)、EGFR为其中关键靶点,且衢枳壳中5个活性成分与核心靶点经分子对接后的结合活性较好。结论衢枳壳中的芦丁、新橙皮苷、橙皮苷、芸香柚皮苷、川陈皮素等可能为衢枳壳降糖的物质基础,可能是通过调控HIF-1、AGE-RAGE、EGFR等信号通路及AKT1、ALB、TP53等核心基因发挥降糖作用。
文摘After decades of theoretical studies,the rich phase states of active matter and cluster kinetic processes are still of research interest.How to efficiently calculate the dynamical processes under their complex conditions becomes an open problem.Recently,machine learning methods have been proposed to predict the degree of coherence of active matter systems.In this way,the phase transition process of the system is quantified and studied.In this paper,we use graph network as a powerful model to determine the evolution of active matter with variable individual velocities solely based on the initial position and state of the particles.The graph network accurately predicts the order parameters of the system in different scale models with different individual velocities,noise and density to effectively evaluate the effect of diverse condition.Compared with the classical physical deduction method,we demonstrate that graph network prediction is excellent,which could save significantly computing resources and time.In addition to active matter,our method can be applied widely to other large-scale physical systems.
文摘Author present the interplay between different neuron types in the spontaneous electrical activity of low density cortical in vitro networks grown on MEA (multielectrode arrays) of glass neurochips. In 10% of the networks, the continuously spiking activity of some neurons was inhibited by synchronous bursts or superbursts of the majority of the other neurons. Immunohistochemical staining subsequent to MEA recordings suggest that the synchronously bursting neurons are parvalbumin-positive interneurons with abundant axonal ramifications. Blocking chemical synaptic transmission by Ca2+-free medium revealed that the curbed spiking neurons are intrinsically active. It is assumed that these neurons are pyramidal cells which may be inhibited by groups of synchronously bursting interneurons. It is propose that the observed burst-induced inhibition is an important principle in the temporal organization of neuronal activity as well as in the restriction of excitation, and thus essential for information processing in the cerebral cortex.
文摘With the expansion of distributed generation systems and demand response programs, the need to fully utilize distribution system capacity has increased. In addition, the potential bidirectional flow of power on distribution networks demands voltage visibility and control at all voltage levels. Distribution system state estimations, however, have traditionally been less prioritized due to the lack of enough measurement points while being the major role player in knowing the real-time system states of active distribution networks. The advent of smart meters at LV loads, on the other hand, is giving relief to this shortcoming. This study explores the potential of bottom up load flow analysis based on customer level Automatic Meter Reading (AMRs) to compute short time forecasts of demands and distribution network system states. A state estimation frame-work, which makes use of available AMR data, is proposed and discussed.