Estimating the subsolar magnetopause position from soft X-ray images using a low-pass image filter

The Lunar Environment heliospheric X-ray Imager(LEXI)and Solar wind Magnetosphere Ionosphere Link Explorer(SMILE)missions will image the Earth’s dayside magneto pause and cusps in soft X-rays after their respective launches in the near future,to specify glo bal magnetic reconnection modes for varying solar wind conditions.To suppo rt the success of these scientific missions,it is critical to develop techniques that extract the magnetopause locations from the observed soft X-ray images.In this research,we introduce a new geometric equation that calculates the subsolar magnetopause position(RS)from a satellite position,the look direction of the instrument,and the angle at which the X-ray emission is maximized.Two assumptions are used in this method:(1)The look direction where soft X-ray emissions are maximized lies tangent to the magnetopause,and(2)the magnetopause surface near the subsolar point is almost spherical and thus RSis nea rly equal to the radius of the magneto pause curvature.We create synthetic soft X-ray images by using the Open Geospace General Circulation Model(OpenGGCM)global magnetohydrodynamic model,the galactic background,the instrument point spread function,and Poisson noise.We then apply the fast Fourier transform and Gaussian low-pass filte rs to the synthetic images to re move noise and obtain accurate look angles for the soft X-ray pea ks.From the filte red images,we calculate RS and its accuracy for different LEXI locations,look directions,and solar wind densities by using the OpenGGCM subsolar magnetopause location as ground truth.Our method estimates RS with an accuracy of<0.3 RE when the solar wind density exceeds>10 cm-3.The accuracy improves for greater solar wind densities and during southward interplanetary magnetic fields.The method ca ptures the magnetopause motion during southwa rd interplaneta ry magnetic field turnings.Consequently,the technique will enable quantitative analysis of the magnetopause motion and help reveal the dayside reconnection modes for dynamic solar wind conditions.This technique will suppo rt the LEXI and SMILE missions in achieving their scientific o bjectives.

Novel Double Modular Redundancy Based Fault-Tolerant FIR Filter for Image Denoising

In signal processing and communication systems,digital filters are widely employed.In some circumstances,the reliability of those systems is crucial,necessitating the use of fault tolerant filter implementations.Many strategies have been presented throughout the years to achieve fault tolerance by utilising the structure and properties of the filters.As technology advances,more complicated systems with several filters become possible.Some of the filters in those complicated systems frequently function in parallel,for example,by applying the same filter to various input signals.Recently,a simple strategy for achieving fault tolerance that takes advantage of the availability of parallel filters was given.Many fault-tolerant ways that take advantage of the filter’s structure and properties have been proposed throughout the years.The primary idea is to use structured authentication scan chains to study the internal states of finite impulse response(FIR)components in order to detect and recover the exact state of faulty modules through the state of non-faulty modules.Finally,a simple solution of Double modular redundancy(DMR)based fault tolerance was developed that takes advantage of the availability of parallel filters for image denoising.This approach is expanded in this short to display how parallel filters can be protected using error correction codes(ECCs)in which each filter is comparable to a bit in a standard ECC.“Advanced error recovery for parallel systems,”the suggested technique,can find and eliminate hidden defects in FIR modules,and also restore the system from multiple failures impacting two FIR modules.From the implementation,Xilinx ISE 14.7 was found to have given significant error reduction capability in the fault calculations and reduction in the area which reduces the cost of implementation.Faults were introduced in all the outputs of the functional filters and found that the fault in every output is corrected.

Retroperitoneal hematoma after implantation of double inferior vena cava filters

A 55-year-old man developed deep venous thrombosis and inferior vena cava(IVC) thrombosis 7 years earlier and was treated by placement of a permanent IVC filter. One week ago, he was admitted with bilateral lower limb swelling and pain. Digital subtraction angiography showed a filling defect above the original filter. A retrievable Tulip filter was placed and catheter-directed thrombolysis was performed. Six days later, the patient experienced sudden, persistent upper right abdominal pain, and a computed tomography scan revealed the formation of retroperitoneal hematoma. Symptomatic treatments were administered, and the hematoma gradually resolved during follow-up.

On Filters of Double MS-algebras

Here some properties on filters of double MS-algebras are descripted. We show that,for a normal filter F of a double MS-algebra (L;0, + )(x,y) ∈θ(F) (a,b ∈ F) (x ∧α)∨b+= (y ∧ a)∨ b+.

On low-pass digital filters in oceanography

-Two types of filters are widely used to remove semidirunal and diurnal tidal signals and other high frequency noises in oceanography. The first type of filters uses moving average with weights in time domain, and can be easily operated. Some data will be lost at each end of the time series, especially for the low low-pass filters. The second type of filters uses the discrete Fourier transform filter (DFTF) which operates in the frequency domain, and there are no data loss at the ends for the forward transform. However, owing to the Gibbs phenomenon and the discrete sampling (Nyquist effect) , ringing appears in the inverse transformed data, which is especially serious at each end. Thus some data at the ends are also discarded. The present study tries to find out what causes the ringing and then to seek for methods to overcome the ringing. We have found that there are two kinds of ringings, one is the Gibbs phenomenon, as defined before. The other is the 'Nyquist'ringing due to sampling Nyquist critical frequency. The former is due to the abrupt transition in frequency band. The Gibbs and Nyquist effects show the ringing at each end of the filtered time series. Thus, the use of a cosine taper or a linear taper on the window in the frequency domain makes the transition band smooth, so that the Gibbs phenomenon will be minimized. Before applying the Fast Fourier Transform (FFT), the original time series at each end is properly tapered by a split cosine bell that reduces significant ringing since this method limits the energy transfer from outside of the Nyquist frequency. Thus, the DFTF can be a powerful tool to suppress the signals in which we are not interested, with sharp peaks in low frequency variation and less data loss at each end.

Uncertainties of landslide susceptibility prediction: Influences of random errors in landslide conditioning factors and errors reduction by low pass filter method

In the existing landslide susceptibility prediction(LSP)models,the influences of random errors in landslide conditioning factors on LSP are not considered,instead the original conditioning factors are directly taken as the model inputs,which brings uncertainties to LSP results.This study aims to reveal the influence rules of the different proportional random errors in conditioning factors on the LSP un-certainties,and further explore a method which can effectively reduce the random errors in conditioning factors.The original conditioning factors are firstly used to construct original factors-based LSP models,and then different random errors of 5%,10%,15% and 20%are added to these original factors for con-structing relevant errors-based LSP models.Secondly,low-pass filter-based LSP models are constructed by eliminating the random errors using low-pass filter method.Thirdly,the Ruijin County of China with 370 landslides and 16 conditioning factors are used as study case.Three typical machine learning models,i.e.multilayer perceptron(MLP),support vector machine(SVM)and random forest(RF),are selected as LSP models.Finally,the LSP uncertainties are discussed and results show that:(1)The low-pass filter can effectively reduce the random errors in conditioning factors to decrease the LSP uncertainties.(2)With the proportions of random errors increasing from 5%to 20%,the LSP uncertainty increases continuously.(3)The original factors-based models are feasible for LSP in the absence of more accurate conditioning factors.(4)The influence degrees of two uncertainty issues,machine learning models and different proportions of random errors,on the LSP modeling are large and basically the same.(5)The Shapley values effectively explain the internal mechanism of machine learning model predicting landslide sus-ceptibility.In conclusion,greater proportion of random errors in conditioning factors results in higher LSP uncertainty,and low-pass filter can effectively reduce these random errors.

Filtering-efficiency measurement of Chinese-made filter 1by double-filter method

Filtering efficiency of the Chinese-made filter 1 has been measured by the double-filter method with only one set of measurement equipment. The β counts of the two filters are measured in turn for every 3 minutes, from which the decay constants are extracted to be 0.0131 min-1 and 0.0129 min-1 for the first and second filter respectively. After correcting the β counts of the second filter, the filtering efficiency of the filter is obtained to be (87.4±0.7)% in average.

Comparative Study of Low-Pass Filter and Phase-Locked Loop Type Speed Filters for Sensorless Control of AC Drives

High quality speed information is one of the key issues in machine sensorless drives,which often requires proper filtering of the estimated speed.This paper comparatively studies typical low-pass filters(LPF)and phase-locked loop(PLL)type filters with respect to ramp speed reference tracking and steady-state performances,as well as the achievement of adaptive cutoff frequency control.An improved LPF-based filter structure with no ramping and steady-state errors caused by filter parameter quantization effects is proposed,which is suitable for applying LPF for sensorless drives of AC machines,especially when fixed-point digital signal processor is selected e.g.in mass production.Furthermore,the potential of adopting PLL for speed filtering is explored.It is demonstrated that PLL type filters can well maintain the advantages offered by the improved LPF.Moreover,it is found that the PLL type filters exhibit almost linear relationship between the cutoff frequency of the PLL filter and its proportional-integral(PI)gains,which can ease the realization of speed filters with adaptive cutoff frequency for improving the speed transient performance.The proposed filters are verified experimentally.The PLL type filter with adaptive cutoff frequency can provide satisfactory performances under various operating conditions and is therefore recommended.

Research on SINS Alignment Algorithm Based on FIR Filters

An inertial frame based alignment (IFBA) method is presented, especially for the applications on a rocking platform, e.g., marine applications. Defining the initial body frame as the inertial frame, the IFBA method achieves the alignment by virtue of a cascade of low-pass FIR filters, which attenuate the disturbing acceleration and maintain the gravity vector. The aligning time rests with the orders of the FIR filter group, and the method is suitable for large initial misalignment case. An alignment scheme comprising a coarse phase by the IFBA method and a fine phase by a Kalman filter is presented. Both vehicle-based and ship-based alignment experiments were carried out. The results show that the proposed scheme converges much faster than the traditional method at no cost of precision and also works well under any large initial misalignment.

Spin-polarized current in double quantum dots

We analyze the transport through asymmetric double quantum dots with an inhomogeneous Zeeman splitting in the presence of crossed dc and ac magnetic fields. A strong spin-polarized current can be obtained by changing the dc magnetic field. It is mainly due to the resonant tunnelling. But for the ferromagnetic right electrode, the electron spin resonance also plays an important role in transport. We show that the double quantum dots with three-level mixing under crossed dc and ac magnetic fields can act not only as a bipolar spin filter but also as a spin inverter under suitable conditions.

Design of low-pass filter based on a novel defected ground structure

A novel defected ground structure （DGS） for the microstrip line is proposed in this paper. The DGS lattice has more defect parameters so that it can provide better performance than the conventional dumbbell-shaped DGS. Selectivity is improved by 97.2% with a sharpness factor of 24.6%. The method is applied to the design of a low-pass filter to confirm validity of the proposed DGS.

Compact Metamaterial Microstrip Low-Pass Filter

Complimentary hexagonal-omega structures are used to design compact, low insertion loss (IL), low pass filter with sharp cut-off. It has been designed for improvement of roll-off performance based on both μ and ε negative property of the complimentary hex-omega structure while maintaining the filter pass-band performance. By properly designing and loading the hexagonal-omega structure in the ground of microstrip line not only improve the roll-off of the low pass filter, but also reduced the filter size. The simulated results indicate that the proposed filter achieves a flat pass band with no ripples as well as selectivity of 19.68 dB/GHz, corresponding to 5-unit cells hex-omega structures. This significantly exceeds the 5.6 dB/GHz selectivity of the conventional low pass filter design, due to sub-lambda dimensions of the hex-omega structure. A prototype filter implementing area is: 0.712λg x 0.263λg, λg being the guided wavelength at 3-dB cut-off frequency (fc). The proposed filter has a size smaller by 36.2%.

Microstrip Low-Pass Elliptic Filter Design Based on Implicit Space Mapping Optimization

It is a time-consuming and often iterative procedure to determine design parameters based on fine, accurate but expensive, models. To decrease the number of fine model evaluations, space mapping techniques may be employed. In this approach, it is assumed both fine model and coarse, fast but inaccurate, one are available. First, the coarse model is optimized to obtain design parameters satisfying design objectives. Next, auxiliary parameters are calibrated to match coarse and fine models’ responses. Then, the improved coarse model is re-optimized to obtain new design parameters. The design procedure is stopped when a satisfactory solution is reached. In this paper, an implicit space mapping method is used to design a microstrip low-pass elliptic filter. Simulation results show that only two fine model evaluations are sufficient to get satisfactory results.

On Some <i>I</i>-Convergent Double Sequence Spaces Defined by a Modulus Function

In 2000, Kostyrko, Salat, and Wilczynski introduced and studied the concept of I-convergence of sequences in metric spaces where I is an ideal. The concept of I-convergence has a wide application in the field of Number Theory, trigonometric series, summability theory, probability theory, optimization and approximation theory. In this article we introduce the double sequence spaces and ,for a modulus function f and study some of the properties of these spaces.

Design Consideration and Reconstruction Method for Double-source Double-multislice Spiral CT

To accelerate the scan speed and improve the image quality, a new type of CT configuration, "double-source double-multislice spiral CT" (DSDMS-CT), which is based on two sets of single-source multislice spiral CT was proposed with a special reconstruction algorithm. Simulation results using the fan-beam filtered backprojection algorithm with a special interpolation method were presented for both single-source multislice spiral CT and DSDMS-CT. The results of new CT model show that it scans faster than the traditional spiral CT and has a better slice sensitivity profile (SSP) with larger pitch value.

双重伪补Ockham代数的理想与滤子的构造

序代数理论在理论计算机、多值逻辑学、信息系统科学等方面有着广泛且重要的应用。在序代数研究领域,理想和滤子是刻画代数结构的重要工具。双重伪补Ockham代数是在双重伪补代数和Ockham代数基础上定义的一类新的代数类,基于双重伪补Ockham代数的运算规律以及双重伪补运算与Ockham代数运算的关联性,对双重伪补Ockham代数的理想与滤子做进一步的研究。首先,运用Ockham代数的运算构造出双重伪补Ockham代数的滤子,并探讨了相关性质。其次,借助于双重伪补Ockham代数核理想和余核滤子的充要条件构造出了核理想和余核滤子的具体集合形式。所得结论为其他序代数类的理想和滤子性质的研究提供了方法,也将有助于进一步探索序代数理论在其他学科如模糊集、计算机科学中的应用。

一种适用于复杂电网下的高精度锁相环

针对现有并网逆变器在电网电压谐波复杂的情况下难以精确锁定电压频率和相位的问题,结合传统锁相环结构与自适应算法的理论提出一种高精度的锁相方法。依据对传统锁相环在复杂电网下的弊端分析,确定了锁相环采用传统低通滤波器、带通滤波器时的滤波效果与延时的矛盾关系。根据最小均方算法的高自适应特性与快速跟踪特点,结合锁相环中坐标变换公式,确定算法的输入输出以及权重矩阵,构建基于派克变换的最小均方算法矩阵模型。通过将所需的电压正序分量设置为不断更新的权重矩阵来进行高精度的滤波,同时通过引入均方瞬时误差和自相关估计均值来进行变步长控制,提高滤波更新速度,以适用于复杂程度不确定的电网电压进行自适应滤波锁相。对仿真和样机实验的结果表明:采用基于派克变换的最小均方算法的改进型双二阶广义积分锁相方法,可以在不降低动态响应速度的前提下,提高锁相环的滤波效果,进而提高并网逆变器在电网畸变严重场景下锁定电压频率和相位的跟踪精度。

多谐波源接入的城市配电网SAPF优化配置方法

针对分布式光伏和电动汽车充电设施等新谐波源渗透率高及分散接入造成的城市配电网谐波污染分散化与全网化问题,构建一种兼顾配电网谐波治理成本与治理成效的并联型有源电力滤波器选址定容双层优化模型。首先,外、内层模型分别以配电网谐波治理成本最小和电压畸变率最低为目标函数;然后,采用粒子群优化算法和遗传算法分别求解,实现配电网谐波治理效益最高的目标;最后,选取IEEE 33节点系统进行仿真,验证了所建模型对配电网谐波治理装置优化配置的有效性。

PMF+双门限Tong检测的北斗B1I信号捕获算法

针对传统Tong检测算法检测时间长、漏警概率大的问题,提出将PMF+双门限Tong检测算法应用于北斗B1I信号的捕获中。首先,将射频前端模块处理得到的中频信号下变频至基带,对基带信号进行降速等预处理;然后,利用部分匹配滤波(PMF)算法计算相关值,通过PMF算法将数据信号分成几个均等片段,对每一段信号都分别计算相关值,会出现三组具有同相位的相关结果;最后,利用双门限Tong检测算法对PMF算法计算得到的相关结果检测,达到捕获B1I信号的目的。仿真结果表明,利用该算法捕获北斗B1I信号,有效提高了捕获时的检测概率并缩短了检测时间,提高了捕获B1I信号的速度。

基于改性粉煤灰材料的双滤筒VOCs吸附装置开发

针对挥发性有机物(VOCs)污染,基于改性粉煤灰材料的理化性质设计了一种新型VOCs高效吸附装置。采用改性粉煤灰为吸附剂,其成本低廉且再生操作简单;内外双滤桶设计大大增加了被处理气体和吸附剂的接触面积;旋转上升的气流设计使气压分配均匀,避免沟流的出现,减小死层厚度,提高吸附剂的利用率;设有再生装置,吸附剂可与滤筒整体更换,避免散料运输时造成二次污染。本装置贴近工业生产气体处理实际,是一种可实现VOCs高效捕集及回收、吸附剂反复利用的VOCs处理新工艺。