The Intelligent Grouping and Resource Sharing(IGRS)standard is set to enable intelligent grouping,resource sharing and services collaboration among information devices.An IGRS system adopts open architecture,that is,t...The Intelligent Grouping and Resource Sharing(IGRS)standard is set to enable intelligent grouping,resource sharing and services collaboration among information devices.An IGRS system adopts open architecture,that is,the devices abide by the IGRS standard are interoperable with devices following other standards such as Universal Plug and Play(UPnP).The IGRS supports multiple application frameworks and special applications.Developers can use an IGRS media application framework with various media format standards,such as AVS and MPEG-2,to develop multimedia applications.Applied among computers,consumer electronics,and communication devices,the IGRS standard can realize resource sharing and services collaboration in a certain range of wired or wireless network domain.展开更多
This paper presents a Shared Control Architecture(SCA)between a human pilot and a smart inceptor for nonlinear Pilot Induced Oscillations(PIOs),e.g.,category II or III PIOs.One innovation of this paper is that an inte...This paper presents a Shared Control Architecture(SCA)between a human pilot and a smart inceptor for nonlinear Pilot Induced Oscillations(PIOs),e.g.,category II or III PIOs.One innovation of this paper is that an intelligent shared control architecture is developed based on the intelligent active inceptor technique,i.e.,Smart Adaptive Flight Effective Cue(SAFE-Cue).A deep reinforcement learning approach namely Deep Deterministic Policy Gradient(DDPG)method is chosen to design a gain adaptation mechanism for the SAFE-Cue module.By doing this,the gains of the SAFE-Cue will be intelligently tuned once nonlinear PIOs triggered;meanwhile,the human pilot will receive a force cue from the SAFE-Cue,and will consequently adapting his/her control policy.The second innovation of this paper is that the reward function of the DDPG based gain adaptation approach is constructed according to flying qualities.Under the premise of considering failure situation,task completion qualities and pilot workload are also taken into account.Finally,the proposed approach is validated using numerical simulation experiments with two types of scenarios:lower actuator rate limits and airframe damages.The Inceptor Peak Power-Phase(IPPP)metric is adopted to analyze the human-vehicle system simulation results.Results and analysis show that the DDPG based sharing control approach can well address nonlinear PIO problems consisting of Categories Ⅱ and Ⅲ PIO events.展开更多
This paper introduces the operational characteristics of the era of big data and the current era of big data challenges, and exhaustive research and design of big data analytics platform based on cloud computing, incl...This paper introduces the operational characteristics of the era of big data and the current era of big data challenges, and exhaustive research and design of big data analytics platform based on cloud computing, including big data analytics platform architecture system, big data analytics platform software architecture, big data analytics platform network architecture big data analysis platform unified program features and so on. The paper also analyzes the cloud computing platform for big data analysis program unified competitive advantage and development of business telecom operators play a certain role in the future.展开更多
Background:Despite a strong link between obstructive sleep apnea(OSA)and sleep traits,the shared genetic architecture remains unclear.This study aims to explore the shared genetic basis and bidirectional causal betwee...Background:Despite a strong link between obstructive sleep apnea(OSA)and sleep traits,the shared genetic architecture remains unclear.This study aims to explore the shared genetic basis and bidirectional causal between OSA and sleep traits.Methods:Using large‐scale genome‐wide association studies summary statistics for OSA and sleep traits,we employed linkage disequilibrium score regression(LDSR)and MiXeR to examine genetic correlations and quantify polygenic overlaps.The causal association was explored by bidirectional Mendelian randomization.In addition,we identified shared genomic loci through conditional and conjunctional false discovery rate(cond/conjFDR)analysis,followed by annotation to identify shared genes.Finally,we performed enrichment,developmental trajectory,and phenome-wide association study analysis of the shared genes to explore underlying mechanisms.Results:We found that both LDSR and MiXeR results revealed substantial genetic correlations and polygenic overlaps between OSA and most of sleep traits.MR analysis supported bidirectional causality between OSA and sleep traits such as insomnia and snoring.Subsequent conjFDR analysis pinpointed 168 distinct shared loci,which encompassed 695 unique genes,and these genes are predominantly enriched in the neurodevelopmental and metabolic process pathways.Notably,the expression of 38 shared genes exhibits a significant correlation with both OSA and sleep traits.These shared genes exhibit specific developmental trajectories and demonstrate significant pleiotropic associations with phenotypes such as metabolism,immunity,and brain structure.Conclusion:This study uncovers the broad pleiotropy of the genetic architecture shared between OSA and sleep traits,highlighting neurodevelopmental and metabolic pathways as the key shared biological underpinnings.展开更多
Non-binary low density parity check （NB-LDPC） codes are considered as preferred candidate in conditions where short/medium codeword length codes and better performance at low signal to noise ratios （SNR） are requi...Non-binary low density parity check （NB-LDPC） codes are considered as preferred candidate in conditions where short/medium codeword length codes and better performance at low signal to noise ratios （SNR） are required. They have better burst error correcting performance, especially with high order Galois fields （GF）. A shared comparator （SCOMP） architecture for elementary of check node （ECN）/elementary of variable node （EVN） to reduce decoder complexity is introduced because high complexity of check node （CN） and variable node （VN） prevent NB-LDPC decoder from widely applications. The decoder over GF（16） is based on the extended rain-sum （EMS） algorithm. The decoder matrix is an irregular structure as it can provide better performance than regular ones. In order to provide higher throughput and increase the parallel processing efficiency, the clock which is 8 times of the system frequency is adopted in this paper to drive the CN/VN modules. The decoder complexity can be reduced by 28% from traditional decoder when SCOMP architecture is introduced. The result of synthesis software shows that the throughput can achieve 34 Mbit/s at 10 iterations. The proposed architecture can be conveniently extended to GF such as GF（64） or GF（256）. Compared with previous works, the decoder proposed in this paper has better hardware efficiency for practical applications.展开更多
文摘The Intelligent Grouping and Resource Sharing(IGRS)standard is set to enable intelligent grouping,resource sharing and services collaboration among information devices.An IGRS system adopts open architecture,that is,the devices abide by the IGRS standard are interoperable with devices following other standards such as Universal Plug and Play(UPnP).The IGRS supports multiple application frameworks and special applications.Developers can use an IGRS media application framework with various media format standards,such as AVS and MPEG-2,to develop multimedia applications.Applied among computers,consumer electronics,and communication devices,the IGRS standard can realize resource sharing and services collaboration in a certain range of wired or wireless network domain.
基金co-supported by the Fundamental Research Funds for the Central Universities of China(No.YWF-23-SDHK-L-005)the 1912 Project,China and the Aeronautical Science Foundation of China(No.20220048051001).
文摘This paper presents a Shared Control Architecture(SCA)between a human pilot and a smart inceptor for nonlinear Pilot Induced Oscillations(PIOs),e.g.,category II or III PIOs.One innovation of this paper is that an intelligent shared control architecture is developed based on the intelligent active inceptor technique,i.e.,Smart Adaptive Flight Effective Cue(SAFE-Cue).A deep reinforcement learning approach namely Deep Deterministic Policy Gradient(DDPG)method is chosen to design a gain adaptation mechanism for the SAFE-Cue module.By doing this,the gains of the SAFE-Cue will be intelligently tuned once nonlinear PIOs triggered;meanwhile,the human pilot will receive a force cue from the SAFE-Cue,and will consequently adapting his/her control policy.The second innovation of this paper is that the reward function of the DDPG based gain adaptation approach is constructed according to flying qualities.Under the premise of considering failure situation,task completion qualities and pilot workload are also taken into account.Finally,the proposed approach is validated using numerical simulation experiments with two types of scenarios:lower actuator rate limits and airframe damages.The Inceptor Peak Power-Phase(IPPP)metric is adopted to analyze the human-vehicle system simulation results.Results and analysis show that the DDPG based sharing control approach can well address nonlinear PIO problems consisting of Categories Ⅱ and Ⅲ PIO events.
文摘This paper introduces the operational characteristics of the era of big data and the current era of big data challenges, and exhaustive research and design of big data analytics platform based on cloud computing, including big data analytics platform architecture system, big data analytics platform software architecture, big data analytics platform network architecture big data analysis platform unified program features and so on. The paper also analyzes the cloud computing platform for big data analysis program unified competitive advantage and development of business telecom operators play a certain role in the future.
基金National Natural Science Foundation of China,Grant/Award Number:82471506Basic and Applied Basic Research Foundation of Guangdong Province,Grant/Award Numbers:2024A1515012967,2025B1515020036+3 种基金Science and Technology Projects in Guangzhou,Grant/Award Number:2030206Planed Science and Technology Projects of Guangzhou,Grant/Award Number:2023A03J0836Guangzhou Municipal Key Discipline in Medicine,Guangzhou High-level Clinical Key Specialty,and Guangzhou Research-oriented HospitalGuangzhou Municipal Science and Technology Bureau,Grant/Award Numbers:2025A03J3353,2025A04J3391。
文摘Background:Despite a strong link between obstructive sleep apnea(OSA)and sleep traits,the shared genetic architecture remains unclear.This study aims to explore the shared genetic basis and bidirectional causal between OSA and sleep traits.Methods:Using large‐scale genome‐wide association studies summary statistics for OSA and sleep traits,we employed linkage disequilibrium score regression(LDSR)and MiXeR to examine genetic correlations and quantify polygenic overlaps.The causal association was explored by bidirectional Mendelian randomization.In addition,we identified shared genomic loci through conditional and conjunctional false discovery rate(cond/conjFDR)analysis,followed by annotation to identify shared genes.Finally,we performed enrichment,developmental trajectory,and phenome-wide association study analysis of the shared genes to explore underlying mechanisms.Results:We found that both LDSR and MiXeR results revealed substantial genetic correlations and polygenic overlaps between OSA and most of sleep traits.MR analysis supported bidirectional causality between OSA and sleep traits such as insomnia and snoring.Subsequent conjFDR analysis pinpointed 168 distinct shared loci,which encompassed 695 unique genes,and these genes are predominantly enriched in the neurodevelopmental and metabolic process pathways.Notably,the expression of 38 shared genes exhibits a significant correlation with both OSA and sleep traits.These shared genes exhibit specific developmental trajectories and demonstrate significant pleiotropic associations with phenotypes such as metabolism,immunity,and brain structure.Conclusion:This study uncovers the broad pleiotropy of the genetic architecture shared between OSA and sleep traits,highlighting neurodevelopmental and metabolic pathways as the key shared biological underpinnings.
基金supported by the Foundation of the Chinese Academy of Sciences (KGFZD-135-16-015)
文摘Non-binary low density parity check （NB-LDPC） codes are considered as preferred candidate in conditions where short/medium codeword length codes and better performance at low signal to noise ratios （SNR） are required. They have better burst error correcting performance, especially with high order Galois fields （GF）. A shared comparator （SCOMP） architecture for elementary of check node （ECN）/elementary of variable node （EVN） to reduce decoder complexity is introduced because high complexity of check node （CN） and variable node （VN） prevent NB-LDPC decoder from widely applications. The decoder over GF（16） is based on the extended rain-sum （EMS） algorithm. The decoder matrix is an irregular structure as it can provide better performance than regular ones. In order to provide higher throughput and increase the parallel processing efficiency, the clock which is 8 times of the system frequency is adopted in this paper to drive the CN/VN modules. The decoder complexity can be reduced by 28% from traditional decoder when SCOMP architecture is introduced. The result of synthesis software shows that the throughput can achieve 34 Mbit/s at 10 iterations. The proposed architecture can be conveniently extended to GF such as GF（64） or GF（256）. Compared with previous works, the decoder proposed in this paper has better hardware efficiency for practical applications.
