Short-Term Rolling Prediction of Tropical Cyclone Intensity Based on Multi-Task Learning with Fusion of Deviation-Angle Variance and Satellite Imagery

Tropical cyclones(TCs)are one of the most serious types of natural disasters,and accurate TC activity predictions are key to disaster prevention and mitigation.Recently,TC track predictions have made significant progress,but the ability to predict their intensity is obviously lagging behind.At present,research on TC intensity prediction takes atmospheric reanalysis data as the research object and mines the relationship between TC-related environmental factors and intensity through deep learning.However,reanalysis data are non-real-time in nature,which does not meet the requirements for operational forecasting applications.Therefore,a TC intensity prediction model named TC-Rolling is proposed,which can simultaneously extract the degree of symmetry for strong TC convective cloud and convection intensity,and fuse the deviation-angle variance with satellite images to construct the correlation between TC convection structure and intensity.For TCs'complex dynamic processes,a convolutional neural network(CNN)is used to learn their temporal and spatial features.For real-time intensity estimation,multi-task learning acts as an implicit time-series enhancement.The model is designed with a rolling strategy that aims to moderate the long-term dependent decay problem and improve accuracy for short-term intensity predictions.Since multiple tasks are correlated,the loss function of 12 h and 24 h are corrected.After testing on a sample of TCs in the Northwest Pacific,with a 4.48 kt root-mean-square error(RMSE)of 6 h intensity prediction,5.78 kt for 12 h,and 13.94 kt for 24 h,TC records from official agencies are used to assess the validity of TC-Rolling.

Joint Retrieval of PM_(2.5) Concentration and Aerosol Optical Depth over China Using Multi-Task Learning on FY-4A AGRI

Aerosol optical depth(AOD)and fine particulate matter with a diameter of less than or equal to 2.5μm(PM_(2.5))play crucial roles in air quality,human health,and climate change.However,the complex correlation of AOD–PM_(2.5)and the limitations of existing algorithms pose a significant challenge in realizing the accurate joint retrieval of these two parameters at the same location.On this point,a multi-task learning(MTL)model,which enables the joint retrieval of PM_(2.5)concentration and AOD,is proposed and applied on the top-of-the-atmosphere reflectance data gathered by the Fengyun-4A Advanced Geosynchronous Radiation Imager(FY-4A AGRI),and compared to that of two single-task learning models—namely,Random Forest(RF)and Deep Neural Network(DNN).Specifically,MTL achieves a coefficient of determination(R^(2))of 0.88 and a root-mean-square error(RMSE)of 0.10 in AOD retrieval.In comparison to RF,the R^(2)increases by 0.04,the RMSE decreases by 0.02,and the percentage of retrieval results falling within the expected error range(Within-EE)rises by 5.55%.The R^(2)and RMSE of PM_(2.5)retrieval by MTL are 0.84 and 13.76μg m~(-3)respectively.Compared with RF,the R^(2)increases by 0.06,the RMSE decreases by 4.55μg m~(-3),and the Within-EE increases by 7.28%.Additionally,compared to DNN,MTL shows an increase of 0.01 in R^(2)and a decrease of 0.02 in RMSE in AOD retrieval,with a corresponding increase of 2.89%in Within-EE.For PM_(2.5)retrieval,MTL exhibits an increase of 0.05 in R^(2),a decrease of 1.76μg m~(-3)in RMSE,and an increase of 6.83%in Within-EE.The evaluation suggests that MTL is able to provide simultaneously improved AOD and PM_(2.5)retrievals,demonstrating a significant advantage in efficiently capturing the spatial distribution of PM_(2.5)concentration and AOD.

MDTCNet:Multi-Task Classifications Network and TCNN for Direction of Arrival Estimation

The direction-of-arrival(DoA) estimation is one of the hot research areas in signal processing. To overcome the DoA estimation challenge without the prior information about signal sources number and multipath number in millimeter wave system,the multi-task deep residual shrinkage network(MTDRSN) and transfer learning-based convolutional neural network(TCNN), namely MDTCNet, are proposed. The sampling covariance matrix based on the received signal is used as the input to the proposed network. A DRSN-based multi-task classifications model is first introduced to estimate signal sources number and multipath number simultaneously. Then, the DoAs with multi-signal and multipath are estimated by the regression model. The proposed CNN is applied for DoAs estimation with the predicted number of signal sources and paths. Furthermore, the modelbased transfer learning is also introduced into the regression model. The TCNN inherits the partial network parameters of the already formed optimization model obtained by the CNN. A series of experimental results show that the MDTCNet-based DoAs estimation method can accurately predict the signal sources number and multipath number under a range of signal-to-noise ratios. Remarkably, the proposed method achieves the lower root mean square error compared with some existing deep learning-based and traditional methods.

A Multi-Task Deep Learning Framework for Simultaneous Detection of Thoracic Pathology through Image Classification

Thoracic diseases pose significant risks to an individual's chest health and are among the most perilous medical diseases. They can impact either one or both lungs, which leads to a severe impairment of a person’s ability to breathe normally. Some notable examples of such diseases encompass pneumonia, lung cancer, coronavirus disease 2019 (COVID-19), tuberculosis, and chronic obstructive pulmonary disease (COPD). Consequently, early and precise detection of these diseases is paramount during the diagnostic process. Traditionally, the primary methods employed for the detection involve the use of X-ray imaging or computed tomography (CT) scans. Nevertheless, due to the scarcity of proficient radiologists and the inherent similarities between these diseases, the accuracy of detection can be compromised, leading to imprecise or erroneous results. To address this challenge, scientists have turned to computer-based solutions, aiming for swift and accurate diagnoses. The primary objective of this study is to develop two machine learning models, utilizing single-task and multi-task learning frameworks, to enhance classification accuracy. Within the multi-task learning architecture, two principal approaches exist soft parameter sharing and hard parameter sharing. Consequently, this research adopts a multi-task deep learning approach that leverages CNNs to achieve improved classification performance for the specified tasks. These tasks, focusing on pneumonia and COVID-19, are processed and learned simultaneously within a multi-task model. To assess the effectiveness of the trained model, it is rigorously validated using three different real-world datasets for training and testing.

航天测控系统中的测速精度分析与鉴定

在航天测控系统中,双向多普勒测速是实现高精度外测的主要体制。为了进一步提升双向多普勒测速的精度,需要对测速误差进行分析与鉴定。针对双向多普勒测速体制中的误差源问题,给出并阐述了发射频率稳定度、接收机本振频率稳定度、热噪声等随机误差,以及信号漂移、多普勒变化率、大气折射等系统误差。对S频段航天测控系统的测速精度进行了误差分析,设计了基于无人机GPS载荷的测速精度鉴定方案,为提升测速精度提供了实践参考。

基于Telemetry架构的数据中心网络纳秒级时间同步

为了解决传统的局部时间同步架构与集中式管理脱节、需要额外交互开销、时间数据较少易受离群值影响等问题,针对数据中心网络的高精准时间同步需求,提出了基于Telemetry架构的纳秒级时间同步系统。该系统借助数据中心的背景流量收集时间信息,结合离群因子检测算法对汇报上来的大量时间信息进行分析处理,达成一种集中式的纳秒级自动同步,便于后续全局网络调度。所提系统在可编程交换机上实现并进行了评估,结果显示在多跳之间及不同链路速率下,节点间均可以达到纳秒级的高精准时间同步。

Multipoint Infrared Telemetry System for Measuring the Piston Temperature in Internal Combustion Engines

A high precision, high antijamming multipoint infrared telemetry system was developed to measure the piston temperature in internal combustion engine. The temperature at the measuring point is converted into corresponding voltage signal by the thermo-couple first. Then after the V/F stage, the voltage signal is converted into the frequency signal to drive the infrared light-emitting diode to transmit infrared pulses. At the receiver end, a photosensitive audion receives the infrared pulses. After conversion, the voltage recorded by the receiver stands for the magnitude of temperature at the measuring point. Test results of the system indicate that the system is practical and the system can perform multipoint looping temperature measurements for the piston.

基于Telemetry的OTN设备性能采集系统研究

【目的】软件定义网络(SDN)设备规模日益增大,承载的业务越来越多。针对传统光传送网(OTN)设备使用简单网络管理协议(SNMP)采集性能数据不能解决大规模和高性能网络管理的问题,文章提出了基于Telemetry架构的OTN设备性能采集系统。【方法】通过设计分布式数据模型转换和数据编码架构,提高数据转换和编码效率以及采集系统的规模,同时均衡设备算力,设备以秒级周期定时采集并上报性能数据到采集器。【结果】文章对使用SNMP和部署Telemetry系统设备的性能采集能力进行了实验对比分析。【结论】结果表明,系统在数据模型转换和编码、数据传输效率、采集数据的时效性以及数据获取的灵活性方面更有优势,满足SDN对智能运维的要求。

随钻声波数据遥传中的声通信仿真研究

实时高效的数据遥传是制约随钻测井发展的关键技术难题.随钻声波遥传技术利用周期钻柱中的声载波传输测井数据,有望突破目前的低速遥传限制.随钻声信道是流固耦合的复杂波导,然而理论模型大多将其简化为自由钻柱,而忽略了充液井孔的耦合效应.本文从信道建模理论出发,构建了基于四端口传播矩阵的全波信道函数,并提出低复杂度的单载波相干声通信方案,从理论上评估了随钻声信道响应特性与传输性能.通过与有限差分法的对比验证了本文信道建模方法的有效性.仿真结果表明:随钻声信道具有离散带隙的幅度特性和非线性失真的相位特性;信道通带内传输的调制载波具有显著的群延迟,补偿后的系统传输性能得到提升;189.5 m信道通带内能实现单载波20 bps的有效数据传输.本文结果为随钻声波遥传提供了理论依据.

Design of programmable high-accuracy telemetric fast collection system

A programmable high-accuracy system was proposed to collect and process telemetric fast varying signals,which consists of pre-circuit,analog-to-digital（A/D）conversion unit and signal collection and processing part.Performance analysis demonstrates that this novel telemetry-acquisition method is a potential solution to rapidly process fast varying signals and efficiently utilize telemetry channel.

基于故障模式与影响分析和工作分解结构方法的遥测监护系统管理模式研究

目的:探讨故障模式与影响分析(FMEA)和工作分解结构(WBS)方法相结合对遥测监护系统管理的应用价值。方法:选取2022年3月至2024年4月湖州市第三人民医院在用的7套遥测监护系统,将2022年3月至2023年2月期间遥测监护系统使用采用常规模式管理,2023年5月至2024年4月期间遥测监护系统使用采用基于FMEA与WBS方法相结合的遥测监护系统管理模式管理。通过FMEA方法分析2022年3月至2023年2月期间遥测监护系统1740次使用中各种故障的风险量化评分,其故障类型用Fx表示,根据故障风险量化评分评出影响系统安全有效使用风险评级最高的射频(RF)信号不佳(F2)、心电图(ECG)伪差干扰大(F3)、血氧饱和度(SpO_(2))测量异常(F6)、患者过度移动及误触(F8)和遥测发射盒身份标识号(ID)错误(F9)5种故障类型,运用WBS质量管理方法结合树形图、对策性鱼骨图和任务分配矩阵等工具进行遥测监护系统管理预期目标设定、对策分析、任务拟定及工作落实,对比2023年5月至2024年4月1850次遥测监护系统使用中风险评级最高的5种故障风险评级变化和故障发生率。结果:遥测监护系统管理模式管理后,风险评级最高的F2、F3、F6、F8和F9故障的风险评级均由高风险评级降至对应的低、中、中、低和中风险评级。遥测监护系统管理后风险评级最高的F2、F3、F6、F8、F9故障和总故障分别发生91、89、39、45、39和478次,发生率分别为4.92%、4.81%、2.11%、2.43%、2.11%和25.84%,均明显低于常规管理方法,差异有统计学意义(χ^(2)=2.125、6.911、9.099、2.261、2.431、32.491,P<0.05)。结论:FMEA与WBS质量管理方法相结合对遥测监护系统进行管理,能够降低设备故障风险评级和故障发生率,保障设备临床使用安全。

Multi-tasking to Address Diversity in Language Learning

With focus now placed on the learner, more attention is given to his learning style, multiple intelligence and developing learning strategies to enable him to make sense of and use of the target language appropriately in varied contexts and with different uses of the language. To attain this, the teacher is tasked with designing, monitoring and processing language learning activities for students to carry out and in the process learn by doing and reflecting on the learning process they went through as they interacted socially with each other. This paper describes a task named"The Fishbowl Technique"and found to be effective in large ESL classes in the secondary level in the Philippines.

复旋转MSD算法性能分析与验证

目前多符号检测和Turbo乘积码译码已广泛应用。针对不同设备在算法处理及工程实现上存在差异,设备实际应用效果不同的问题,经过分析论证,提出复旋转MSD算法应用在某型新研遥测设备上的方案,并分别对多符号检测、Turbo乘积码译码以及两者结合的性能进行了仿真分析。同时,基于设备环境对算法工程实现后的性能进行实测验证。验证结果表明,同等条件下基带复旋转MSD算法增益效果更好。

水文遥测终端技术在水文情报预报中的应用研究

近年来暴雨洪涝极端灾害的频发以及社会经济水平的迅猛发展,使得水文情报预报工作的作用日益突出。水文遥测终端技术作为一项新兴技术,其在水文情报预报中起到十分重要的作用。随着社会的不断发展和科技的进步,水文情报预报工作也应与时俱进,要不断强化现代化技术的应用。基于此,本文根据遥测终端技术工作原理,探究遥测终端技术在水文情报预报中的应用价值和应用要点,以供借鉴。

基于相控阵天线的空基多目标综合测控系统设计

为有效提升靶场空天地一体化的综合测控效能,切实满足高空高速目标以及低空多目标等全维度测控需求,提出基于相控阵天线的空基多目标综合测控系统方案。此系统构建了空天地一体化的立体测控架构,其主体由空基平台、机载测控分系统以及数据中继分系统组成,形成大容量测控信息中继传输的关键节点,具备对多目标全方位遥测信息的接收与转发能力,以及高码率测控信息的中继传输等功能,能够适应诸如高原、海上等复杂地域的快速机动布站要求,攻克了共形天线阵列设计、单元级全数字波束形成以及宽带数据中继通信等一系列关键技术难题,为空天武器靶场的测控工作提供至关重要的支撑与保障。

High resolution tracking of adult horseshoe crabs Limulus polyphemus in a New Hampshire estuary using fixed array ultrasonic telemetry

While several studies have documented the large-scale, seasonal movements of horseshoe crabs, little is known about their fine-scale, daily movement patterns. In this study we used a fixed array ultrasonic telemetry system to track the movements of 12 male and 16 female horseshoe crabs in the Great Bay estuary, New Hampshire. Data were obtained during the mating season, as well as during the remainder of the summer and fall, in the years 2005-2008. During the mating season animals were often, but not always, active during the high tides when they were approaching and leaving the spawning beaches. On average, both males and females approached mating beaches during 33% of the high tides they experienced and they most often made the tran- sition from being inactive to active during the last two hours of an incoming tide. From April-October horseshoe crabs were significantly more active during high tide periods vs low tide periods, with no clear preference for diurnal vs nocturnal activity. After the mating season ended horseshoe crabs continued to move into shallower water at high tide and then return to deeper water at low tide. Observations by SCUBA divers suggest that during these excursions into the mudflats horseshoe crabs were digging pits in the sediment while foraging for food. Thus, the tidal rhythm of activity that has been so well documented during the mating season probably persists into the fall, and primarily involves foraging activities

Small bowel capsule endoscopy in patients with cardiac pacemakers and implantable cardioverter defibrillators:Outcome analysis using telemetry review

AIM:To determine if there were any interactions between cardiac devices and small bowel capsules secondary to electromagnetic interference (EMI) in patients who have undergone small bowel capsule endoscopy (SBCE).METHODS:Authors conducted a chart review of 20 patients with a cardiac pacemaker (CP) or implantable cardioverter defibrillator (ICD) who underwent continuous electrocardiographic monitoring during their SBCE from 2003-2008.authors searched for unexplained electrocardiogram (ECG) findings,changes in CP andICD set parameters,any abnormality in transmitted capsule data,and adverse clinical events.RESULTS:There were no adverse events or hemodynamically significant arrhythmias reported.CP and ICD set parameters were preserved.The majority of ECG abnormalities were also found in pre-or post-SBCE ECG tracings and the CP behavior during arrhythmias appeared appropriate.Two patients seemed to have episodes of undersensing by the CP.However,similar findings were documented in ECGs taken outside the time frame of the SBCE.One patient was observed to have a low signal encountered from the capsule resulting in lack of localization,but no images were lost.CONCLUSION:Capsule-induced EMI remains a possibility but is unlikely to be clinically important.CPinduced interference of SBCE is also possible,but is infrequent and does not result in loss of images transmitted by the capsule.

Seasonal movement of the American horseshoe crab Limulus polyphemus in a semi-enclosed bay on Cape Cod,Massachusetts (USA) as determined by acoustic telemetry

American horseshoe crabs Limulus polyphemus were tracked using acoustic telemetry and traditional tagging in a semi-enclosed bay on Cape Cod （Pleasant Bay）, Massachusetts, USA, to determine seasonal movement patterns. Fifty-five actively spawning females were fitted with transmitters in 2008 and 2009 and were tracked using acoustic telemetry from May 2008 through July 2010. Fil^een crabs with transmitters also had archive depth-temperature tags attached. In addition, over 2000 spawning crabs （males and females） were tagged with US Fish and Wildlife CIdSFWS） button tags over the same period. Ninety-one percent of the crabs with transmitters were detected during this study. In the spring, crabs were primarily located in the northern section of the bay near spawning beaches, whereas in the fall crabs moved towards the deeper portions of the bay, and some may have overwIntered in the bay. There was evidence that a majority （58%-71%） of the females with transmitters spawned in two sequential seasons. One archive tag was recovered resulting in a year-long continuous record of depth and tem- perature data that, when integrated with telemetry data, indicated that the crab overwintered in the bay. The live recapture rate of crabs with USFWS button tags was 11%, with all re-sighted crabs except one observed inside Pleasant Bay. Eighty-three percent of recaptures were found within 2.5kin of the tagging location, and 51% were observed at the same beach where they were tagged. This study provides further evidence that horseshoe crabs in Pleasant Bay may be philopatric to this embayment

Nuclear mass based on the multi-task learning neural network method

The global nuclear mass based on the macroscopic-microscopic model was studied by applying a newly designed multi-task learning artificial neural network(MTL-ANN). First, the reported nuclear binding energies of 2095 nuclei(Z ≥ 8, N ≥ 8) released in the latest Atomic Mass Evaluation AME2020 and the deviations between the fitting result of the liquid drop model(LDM)and data from AME2020 for each nucleus were obtained.To compensate for the deviations and investigate the possible ignored physics in the LDM, the MTL-ANN method was introduced in the model. Compared to the single-task learning(STL) method, this new network has a powerful ability to simultaneously learn multi-nuclear properties,such as the binding energies and single neutron and proton separation energies. Moreover, it is highly effective in reducing the risk of overfitting and achieving better predictions. Consequently, good predictions can be obtained using this nuclear mass model for both the training and validation datasets and for the testing dataset. In detail, the global root mean square(RMS) of the binding energy is effectively reduced from approximately 2.4 MeV of LDM to the current 0.2 MeV, and the RMS of Sn, Spcan also reach approximately 0.2 MeV. Moreover, compared to STL, for the training and validation sets, 3-9% improvement can be achieved with the binding energy, and 20-30% improvement for S_(n), S_(p);for the testing sets, the reduction in deviations can even reach 30-40%, which significantly illustrates the advantage of the current MTL.

Age and sex specific timing, frequency, and spatial distribution of horseshoe crab spawning in Delaware Bay:Insights from a large-scale radio telemetry array

To study horseshoe crab Limulus polyphemus spawning behavior and migration over a large-spatial extent （〉100 km）, we arrayed fixed station radio receivers throughout Delaware Bay and deployed radio transmitters and archival tags on adult horseshoe crabs prior to their spawning season. We tagged and released 160 females and 60 males in 2004 and 217 females in 2005. The array covered approximately 140 km of shoreline. Recapture rates were 〉70% with multi-year recaptures. We categorized adult age by carapace wear. Older females tended to spawn earlier in the season and more frequently than young females, but those tendencies were more apparent in 2004 when spawning overall occurred earlier than in 2005 when spawning was delayed possibly due to decreased water temperatures. Timing of initial spawning within a year was correlated with water temperature. After adjusting for day of first spring tide, the day of In＇st spawning was 4 days earlier for every 1 degree （℃） rise in mean daily water temperature in May. Seventy nine % of spawning occurred during nighttime high tides. Fifty five % of spawning occurred within 3 d of a spring tide, which was slightly higher than the 47% expected if spawning was uniformly distributed regardless of tidal cycle. Within the same spawning season, males and females were observed spawning or intertidally resting at more than one beach separated by 〉5 kin. Between years, most （77%） did not return to spawn at the same beach. Probability of stranding was strongly age dependent for males and females with older adults experiencing higher stranding rates. Horseshoe crabs staging in the shallow waters east of the channel spawned exclusively along the eastern （N J） shoreline, but those staging west of the channel spawned throughout the bay. Overall, several insights emerged from the use of radio telemetry, which advances our understanding of horseshoe crab ecology and will be useful in conserving the Delaware Bay horseshoe crab population and habitats