Anomaly Detection Using Data Rate of Change on Medical Data

The identification and mitigation of anomaly data,characterized by deviations from normal patterns or singularities,stand as critical endeavors in modern technological landscapes,spanning domains such as Non-Fungible Tokens(NFTs),cyber-security,and the burgeoning metaverse.This paper presents a novel proposal aimed at refining anomaly detection methodologies,with a particular focus on continuous data streams.The essence of the proposed approach lies in analyzing the rate of change within such data streams,leveraging this dynamic aspect to discern anomalies with heightened precision and efficacy.Through empirical evaluation,our method demonstrates a marked improvement over existing techniques,showcasing more nuanced and sophisticated result values.Moreover,we envision a trajectory of continuous research and development,wherein iterative refinement and supplementation will tailor our approach to various anomaly detection scenarios,ensuring adaptability and robustness in real-world applications.

Power Splitting Based SWIPT in Network-Coded Two-Way Networks with Data Rate Fairness:An Information-Theoretic Perspective

This paper investigates the simultaneous wireless information and powertransfer(SWIPT) for network-coded two-way relay network from an information-theoretic perspective, where two sources exchange information via an SWIPT-aware energy harvesting(EH) relay. We present a power splitting(PS)-based two-way relaying(PS-TWR) protocol by employing the PS receiver architecture. To explore the system sum rate limit with data rate fairness, an optimization problem under total power constraint is formulated. Then, some explicit solutions are derived for the problem. Numerical results show that due to the path loss effect on energy transfer, with the same total available power, PS-TWR losses some system performance compared with traditional non-EH two-way relaying, where at relatively low and relatively high signalto-noise ratio(SNR), the performance loss is relatively small. Another observation is that, in relatively high SNR regime, PS-TWR outperforms time switching-based two-way relaying(TS-TWR) while in relatively low SNR regime TS-TWR outperforms PS-TWR. It is also shown that with individual available power at the two sources, PS-TWR outperforms TS-TWR in both relatively low and high SNR regimes.

Enhanced Data Transmission Rate of XCTD Profiler Based on OFDM

An expendable conductivity-temperature-depth profiler(XCTD)is one of the most important instruments used to obtain hydrological data,such as temperature and conductivity,and detect ocean depth in a large area.However,the XCTD channel provides poor time-varying performance,narrowband,and low signal-to-noise ratio(SNR),which severely restricts the data transmission rate.In contrast to conventional single-carrier modulation techniques,such as amplitude-shift keying and differential phase-shift keying,this article provides a new method,based on orthogonal frequency division multiplexing(OFDM)to enhance the data transmission rate of deep-sea abandoned profilers.We apply the OFDM to enhance the SNR of the XCTD,which is achieved by reducing the data transmission rate of each sub-channel.Moreover,the bandwidth utilization may be improved by increasing the number of subcarriers in a given bandwidth,which enhances the data transmission rate.Based on analysis of the XCTD channel model,OFDM with different parameters such as constellation mapping,number of subcarriers,subcarrier spacing,signal period and cyclic prefix are achieved.To verify the effectiveness of the OFDM,this study investigates the influence of different parameters on the data transmission rate at different noise levels,i.e.,-20 dB and-40 d B.

Estimation of Sand Transportation Rate for Fixed and Semi-Fixed Dunes Using Meteorological Wind Data

Taibus County, Inner Mongolia, China, lies in a farming-pastoral ecotone, where severe wind erosion and various aeolian sand hazards are prevalent and fixed and semi-fixed sand dunes occur frequently. This study was conducted to investigate the relationships between sand transportation rate and wind speed for the fixed and semi-fixed sand dunes based on field measurements. The annual quantity of soil erosion by wind was estimated using meteorological wind data. The results indicated that the sand transportation rate in Taibus County in 2000 was 57.38 kg cm-1 year-1 for the semi-fixed dunes and 4.56 kg cm-1 year-1 for the fixed dunes. The total duration of erosive winds covered 12.5% of the time of the year, and spring posed the highest potential of sand transportation. Wind with low speed (≤ 17 m s-1) and high frequency plays a dominant role in sand transportation, while strong wind (≥ 17 m s-1) with low frequency significantly enhanced the sand transportation. Erosive wind speed, directions, and frequency were three crucial dynamic factors influencing sand hazards in the farming-pastoral ecotone. The dominant factors intensifying sand and dust storms in Taibus County might be related to the favorable wind condition in combination with the durable drought, which led to land desertification and vegetation degradation.

Maximum Data Generation Rate Routing Protocol Based on Data Flow Controlling Technology for Rechargeable Wireless Sensor Networks

For rechargeable wireless sensor networks,limited energy storage capacity,dynamic energy supply,low and dynamic duty cycles cause that it is unpractical to maintain a fixed routing path for packets delivery permanently from a source to destination in a distributed scenario.Therefore,before data delivery,a sensor has to update its waking schedule continuously and share them to its neighbors,which lead to high energy expenditure for reestablishing path links frequently and low efficiency of energy utilization for collecting packets.In this work,we propose the maximum data generation rate routing protocol based on data flow controlling technology.For a sensor,it does not share its waking schedule to its neighbors and cache any waking schedules of other sensors.Hence,the energy consumption for time synchronization,location information and waking schedule shared will be reduced significantly.The saving energy can be used for improving data collection rate.Simulation shows our scheme is efficient to improve packets generation rate in rechargeable wireless sensor networks.

A new method for improving the inductively coupled data transmission rate of mooring buoy based on carrier signal frequency selection

In the inductively coupled data transmission system of the mooring buoy, the carrier signal frequency of the transmission channel is limited due to the inherent characteristics of the system, resulting in limited channel bandwidth. The limited channel bandwidth limits the increase in inductively coupled data transmission rate.In order to improve the inductively coupled data transmission rate of mooring buoy as much as possible without damaging the data transmission performance, a new method was proposed in this paper. The method is proposed to improve the data transmission rate by selecting the appropriate carrier signal frequencies based on the principle of maximizing the amplitude value of amplitude-frequency characteristic curve of the system. Research has been done according to this method as follows. Firstly, according to the inductively coupled transmission mooring buoy structure, the inductively coupled data transmission circuit model was established. The binary frequency shift keying(2FSK) digital signal modulation mode was selected. Through theoretical analysis, the relation between the carrier signal frequency and the data transmission performance, the relation between the carrier signal frequency and the 2FSK signal bandwidth were obtained. Secondly, the performance and the bandwidth of the signal transmission were studied for the inherent characteristics of the actual inductively coupled data transmission system. The amplitude-frequency characteristic of the system was analyzed by experiments. By selecting the appropriate carrier signal frequency parameters, an excellent data transmission performance was guaranteed and a large 2FSK signal bandwidth was obtained. Finally, an inductively coupled data transmission rate optimization experiment and a bit error rate analysis experiment were designed and carried out. The results show that the high-speed and reliable data transmission of the system was realized and the rate can reach 100 kbps.

Fast Rate Fault Detection Filter for Multirate Sampled-data Systems

This paper focuses on the fast rate fault detection filter (FDF) problem for a class of multirate sampled-data (MSD) systems. A lifting technique is used to convert such an MSD system into a linear time-invariant discrete-time one and an unknown input observer (UIO) is considered as FDF to generate residual. The design of FDF is formulated as an H∞ optimization problem and a solvable condition as well as an optimal solution are derived. The causality of the residual generator can be guaranteed so that the fast rate residual can be implemented via inverse lifting. A numerical example is included to demonstrate the feasibility of the obtained results.

Performance analysis of a class of networked control systems under data rate constraints

In networked control system (NCS) where control loop is closed over communication network, limited data rate may deteriorate control performance even destabilize the control system. In this paper, performance analysis of a typical second-order control system with data rate constraints is conducted, and the concept of critical data rate (CDR) is presented. In order to find the CDR in NCS, an approximate searching method is proposed to guarantee acceptable control performance.

Clustered Federated Learning with Weighted Model Aggregation for Imbalanced Data

As a promising edge learning framework in future 6G networks,federated learning(FL)faces a number of technical challenges due to the heterogeneous network environment and diversified user behaviors.Data imbalance is one of these challenges that can significantly degrade the learning efficiency.To deal with data imbalance issue,this work proposes a new learning framework,called clustered federated learning with weighted model aggregation(weighted CFL).Compared with traditional FL,our weighted CFL adaptively clusters the participating edge devices based on the cosine similarity of their local gradients at each training iteration,and then performs weighted per-cluster model aggregation.Therein,the similarity threshold for clustering is adaptive over iterations in response to the time-varying divergence of local gradients.Moreover,the weights for per-cluster model aggregation are adjusted according to the data balance feature so as to speed up the convergence rate.Experimental results show that the proposed weighted CFL achieves a faster model convergence rate and greater learning accuracy than benchmark methods under the imbalanced data scenario.

A rate-distortion optimized rate shaping scheme for H.264 data partitioned video bitstream

To enable quality sealability and further improve the reconstructed video quallty m rate shaping, a rate-distortion optimized packet dropping scheme for H. 264 data partitioned video bitstream is proposed in this paper. Some side information is generated for each video bitstream in advance, while streaming such side information is exploited by a greedy algorithm to optimally drop partitions in a rate-distortion optimized way. Quality sealability is supported by adopting data partition instead of whole frame as the dropping unit. Simulation resuhs show that the proposed scheme achieves a great gain in the reconstructed video quality over two typical frame dropping schemes, with the help of the fine granularity in dropping unit as well as rate-distortion optimization.

Parameter Estimation Based on Censored Data under Partially Accelerated Life Testing for Hybrid Systems due to Unknown Failure Causes

In general,simple subsystems like series or parallel are integrated to produce a complex hybrid system.The reliability of a system is determined by the reliability of its constituent components.It is often extremely difficult or impossible to get specific information about the component that caused the system to fail.Unknown failure causes are instances in which the actual cause of systemfailure is unknown.On the other side,thanks to current advanced technology based on computers,automation,and simulation,products have become incredibly dependable and trustworthy,and as a result,obtaining failure data for testing such exceptionally reliable items have become a very costly and time-consuming procedure.Therefore,because of its capacity to produce rapid and adequate failure data in a short period of time,accelerated life testing(ALT)is the most utilized approach in the field of product reliability and life testing.Based on progressively hybrid censored(PrHC)data froma three-component parallel series hybrid system that failed to owe to unknown causes,this paper investigates a challenging problem of parameter estimation and reliability assessment under a step stress partially accelerated life-test(SSPALT).Failures of components are considered to follow a power linear hazard rate(PLHR),which can be used when the failure rate displays linear,decreasing,increasing or bathtub failure patterns.The Tempered random variable(TRV)model is considered to reflect the effect of the high stress level used to induce early failure data.The maximum likelihood estimation(MLE)approach is used to estimate the parameters of the PLHR distribution and the acceleration factor.A variance covariance matrix(VCM)is then obtained to construct the approximate confidence intervals(ACIs).In addition,studentized bootstrap confidence intervals(ST-B CIs)are also constructed and compared with ACIs in terms of their respective interval lengths(ILs).Moreover,a simulation study is conducted to demonstrate the performance of the estimation procedures and the methodology discussed in this paper.Finally,real failure data from the air conditioning systems of an airplane is used to illustrate further the performance of the suggested estimation technique.

Probability estimation method for fatigue crack growth rate based on a∼t data from service

Purpose–The study aims to provide a basis for the effective use of safety-related information data and a quantitative assessment way for the occurrence probability of the safety risk such as the fatigue fracture of the key components.Design/methodology/approach–The fatigue crack growth rate is of dispersion,which is often used to accurately describe with probability density.In view of the external dispersion caused by the load,a simple and applicable probability expression of fatigue crack growth rate is adopted based on the fatigue growth theory.Considering the isolation among the pairs of crack length a and crack formation time t(a∼t data)obtained from same kind of structural parts,a statistical analysis approach of t distribution is proposed,which divides the crack length in several segments.Furthermore,according to the compatibility criterion of crack growth,that is,there is statistical development correspondence among a∼t data,the probability model of crack growth rate is established.Findings–The results show that the crack growth rate in the stable growth stage can be approximately expressed by the crack growth control curve da/dt=5 Q•a,and the probability density of the crack growth parameter Q represents the external dispersion;t follows two-parameter Weibull distribution in certain a values.Originality/value–The probability density f(Q)can be estimated by using the probability model of crack growth rate,and a calculation example shows that the estimation method is effective and practical.

Bayesian and Non-Bayesian Analysis for the Sine Generalized Linear Exponential Model under Progressively Censored Data

This article introduces a novel variant of the generalized linear exponential(GLE)distribution,known as the sine generalized linear exponential(SGLE)distribution.The SGLE distribution utilizes the sine transformation to enhance its capabilities.The updated distribution is very adaptable and may be efficiently used in the modeling of survival data and dependability issues.The suggested model incorporates a hazard rate function(HRF)that may display a rising,J-shaped,or bathtub form,depending on its unique characteristics.This model includes many well-known lifespan distributions as separate sub-models.The suggested model is accompanied with a range of statistical features.The model parameters are examined using the techniques of maximum likelihood and Bayesian estimation using progressively censored data.In order to evaluate the effectiveness of these techniques,we provide a set of simulated data for testing purposes.The relevance of the newly presented model is shown via two real-world dataset applications,highlighting its superiority over other respected similar models.

A comprehensive review of heart rate variability as an indicator in the regulation of the autonomic nervous system by acupuncture:a bibliometric analysis

This study sought to conduct a bibliometric analysis of acupuncture studies focusing on heart rate variability(HRV)and to investigate the correlation between various acupoints and their effects on HRV by utilizing association rule mining and network analysis.A total of 536 publications on the topic of acupuncture studies based on HRV.The disease keyword analysis revealed that HRV-related acupuncture studies were mainly related to pain,inflammation,emotional disorders,gastrointestinal function,and hypertension.A separate analysis was conducted on acupuncture prescriptions,and Neiguan(PC6)and Zusanli(ST36)were the most frequently used acupoints.The core acupoints for HRV regulation were identified as PC6,ST36,Shenmen(HT7),Hegu(LI4),Sanyinjiao(SP6),Jianshi(PC5),Taichong(LR3),Quchi(LI11),Guanyuan(CV4),Baihui(GV20),and Taixi(KI3).Additionally,the research encompassed 46 reports on acupuncture animal experiments conducted on HRV,with ST36 being the most frequently utilized acupoint.The research presented in this study offers valuable insights into the global research trend and hotspots in acupuncture-based HRV studies,as well as identifying frequently used combinations of acupoints.The findings may be helpful for further research in this field and provide valuable information about the potential use of acupuncture for improving HRV in both humans and animals.

A Software Reliability Model for OSS Including Various Fault Data Based on Proportional Hazard-Rate Model

The software reliability model is the stochastic model to measure the software reliability quantitatively. A Hazard-Rate Model is the well-known one as the typical software reliability model. We propose Hazard-Rate Models Considering Fault Severity Levels (CFSL) for Open Source Software (OSS). The purpose of this research is to make the Hazard-Rate Model considering CFSL adapt to baseline hazard function and 2 kinds of faults data in Bug Tracking System (BTS), i.e., we use the covariate vectors in Cox proportional Hazard-Rate Model. Also, we show the numerical examples by evaluating the performance of our proposed model. As the result, we compare the performance of our model with the Hazard-Rate Model CFSL.

基于大数据技术的大蒜品质智能化调控研究

以进一步提升大蒜种植的智能性、品质性为目标,选取大数据处理及应用技术,针对大蒜种植过程的调控系统展开设计。考虑大蒜种芽、种植土壤条件等基础特点,结合不同种植调控下的大蒜培育状况,基于大数据架构平台组成,搭建用于智能化品质大蒜调控的数据处理模型。设计布局大数据应用的软件控制模块,配置相应的系统硬件结构,重点针对种芽朝向进行调控。展开品质化作业试验,结果表明:基于大数据技术的大蒜品质智能化调控系统设计,能够很好地运用数据计算与处理算法对大蒜种植运动过程各数据进行准确监测,通过及时的调控措施满足种芽朝向调整正确率要求,单粒合格率可达到95.40%,蒜芽漏充率可降低至3.15%,种植效率相对提升了6.37%,具有很好的推广价值。

基于LoRa的果园管道自动顺序喷雾系统研究

我国南方果园多处于山地,大型喷雾器械无法进入,为实现山地果园自动顺序喷药,设计了一种基于LoRa无线通信技术的管道自动顺序喷雾系统。系统以Stm32单片机为核心,在管网上部署了6个电磁阀控制节点,采用LoRa无线收发模块进行节点之间的通信,设计程序控制6个电磁阀依次按顺序打开,并可以通过手机APP远程开启系统。试验结果表明:当节点之间距离为250 m时,数据接收率为95%;系统通信距离远,数据接收率高,具有较高的可靠性,适合于山地果园中使用。

Contemporary crustal tectonic movement in the southern Sichuan-Yunnan block based on dense GPS observation data

We analyzed 360 permanent and campaign GPS data from 1999 to 2017 in the southern Sichuan-Yunan block, and obtained crustal horizontal deformation in this region.Then, we derived the strain rate using a multi-scale spherical wavelet method.Results reveal a complex pattern of tectonic movement in the southern Sichuan-Yunnan block.Compared to the stable Eurasian plate, the maximum rate of the horizontal deformation in the southern Sichuan-Yunnan block is approximately 22 mm/a.The Xiaojiang fault shows a significantly lower deformation—a left-lateral strike-slip movement of 9.5 mm/a.The Honghe fault clearly shows a complex segmental deformation from the north to south.The northern Honghe fault shows 4.3 mm/a right strike-slip with 6.7 mm/a extension; the southern Honghe fault shows 1.9 mm/a right strike-slip with 1.9 mm/a extension; the junction zone in the Honghe and Lijiang–Xiaojinhe faults shows an obvious clockwise-rotation deformation.The strain calculation results reveal that the maximum shear-strain rate in this region reaches 70 nstrain/a, concentrated around the Xiaojiang fault and at the junction of the Honghe and Lijiang–Xiaojinhe faults.We note that most of the earthquakes with magnitudes of 4 and above that occurred in this region were within the high shear strain-rate zones and the strain rate gradient boundary zone, which indicates that the magnitude of strain accumulation is closely related to the seismic activities.Comparison of the fast shear-wave polarization direction of the upper-crust with the upper-mantle anisotropy and the direction of the surface principal compressive strain rate obtained from the inversion of the GPS data reveals that the direction of the surface principal compressive strain is basically consistent with the fast shear-wave polarization direction of the upper crust anisotropy, but different from the polarization direction of the upper mantle.Our results support the hypothesis that the principal elements of the deformation mechanism in the southern Sichuan-Yunnan block are decoupling between the upper and lower crust and ductile flow in the lower crust.

An automatic identification algorithm for freeway bottleneck based on loop detector data

A bottleneck automatic identification algorithm based on loop detector data is proposed. The proposed algorithm selects the critical flow rate as the trigger variable of the algorithm which is calculated by the road conditions the level of service and the proportion of trucks.The process of identification includes two parts. One is to identify the upstream of the bottleneck by comparing the distance between the current occupancy rate and the mean value of the occupancy rate and the variance of the occupancy rate.The other process is to identify the downstream of the bottleneck by calculating the difference of the upstream occupancy rate with that of the downstream.In addition the algorithm evaluation standards which are based on the time interval of the data the detection rate and the false alarm rate are discussed.The proposed algorithm is applied to detect the bottleneck locations in the Shanghai Inner Ring Viaduct Dabaishu-Guangzhong road section.The proposed method has a good performance in improving the accuracy and efficiency of bottleneck identification.

GF-3 data real-time processing method based on multi-satellite distributed data processing system

Due to the limited scenes that synthetic aperture radar(SAR)satellites can detect,the full-track utilization rate is not high.Because of the computing and storage limitation of one satellite,it is difficult to process large amounts of data of spaceborne synthetic aperture radars.It is proposed to use a new method of networked satellite data processing for improving the efficiency of data processing.A multi-satellite distributed SAR real-time processing method based on Chirp Scaling(CS)imaging algorithm is studied in this paper,and a distributed data processing system is built with field programmable gate array(FPGA)chips as the kernel.Different from the traditional CS algorithm processing,the system divides data processing into three stages.The computing tasks are reasonably allocated to different data processing units(i.e.,satellites)in each stage.The method effectively saves computing and storage resources of satellites,improves the utilization rate of a single satellite,and shortens the data processing time.Gaofen-3(GF-3)satellite SAR raw data is processed by the system,with the performance of the method verified.