Convergence analysis of filtered-X LMS algorithm with secondary path modeling error

A more relaxed sufficient condition for the convergence of filtered-X LMS (FXLMS) algorithm is presented. It is pointed out that if some positive real condition for secondary path transfer function and its estimates is satisfied within all the frequency bands, FXLMS algorithm converges whatever the reference signal is like. But if the above positive real condition is satisfied only within some frequency bands, the convergence of FXLMS algorithm is dependent on the distribution of power spectral density of the reference signal, and the convergence step size is determined by the distribution of some specific correlation matrix eigenvalues.Applying the conclusion above to the Delayed LMS (DLMS) algorithm, it is shown that DLMS algorithm with some error of time delay estimation converges in certain discrete frequency bands, and the width of which are determined only by the 'time-delay estimation error frequency' which is equal to one fourth of the inverse of estimated error of the time delay.

Performance analysis of FXLMS algorithm with secondary path modeling error

Performance analysis of filtered-X LMS (FXLMS) algorithm with secondary path modeling error is carried out in both time and frequency domain. It is shown firstly that the effects of secondary path modeling error on the performance of FXLMS algorithm are determined by the distribution of the relative error of secondary path model along with frequency. In case of that the distribution of relative error is uniform the modeling error of secondary path will have no effects on the performance of the algorithm. In addition, a limitation property of FXLMS algorithm is proved, which implies that the negative effects of secondary path modeling error can be compensated by increasing the adaptive filter length. At last, some insights into the 'spillover' phenomenon of FXLMS algorithm are given.

Robust Fingerprint Construction Based on Multiple Path Loss Model (M-PLM) for Indoor Localization

A robust radio map is essential in implementing a fingerprint-based indoor positioning system(IPS).However,the offline site survey to manually construct the radio map is time-consuming and labour-intensive.Various interpolation techniques have been proposed to infer the virtual fingerprints to reduce the time and effort required for offline site surveys.This paper presents a novel fingerprint interpolator using a multi-path loss model(MPLM)to create the virtual fingerprints from the collected sample data based on different signal paths from different access points(APs).Based on the historical signal data,the poor signal paths are identified using their standard deviations.The proposed method reduces the positioning errors by smoothing out the wireless signal fluctuations and stabilizing the signals for those poor signal paths.By consideringmultipath signal propagations from different APs,the inherent noise from these signal paths can be alleviated.Firstly,locations of the signal data with standard deviations higher than the threshold are identified.The new fingerprints are then generated at these locations based on the proposed M-PLM interpolation function to replace the old fingerprints.The proposed technique interpolates virtual fingerprints based on good signal paths with more stable signals to improve the positioning performance.Experimental results show that the proposed scheme enhances the positioning accuracy by up to 44%compared to the conventional interpolation techniques such as the Inverse DistanceWeighting,Kriging,and single Path LossModel.As a result,we can overcome the site survey problems for IPS by building an accurate radio map with more reliable signals to improve indoor positioning performance.

Path Classification and Estimation Model Based Prognosis of Pneumatic Cylinder Lifetime

Prognosis is a key technology to improve reliability,safety and maintainability of products,a lot of researchers have been devoted to this technology.But to improve the predict accuracy of remaining life of products has been difficult.To predict the lifetime specification of pneumatic cylinders with high reliability and long lifetime and small specimen,this paper put forward the prognosis algorithm based on the path classification and estimation（PACE） model.PACE model is based entirely on failure data instead of failure threshold.Pneumatic cylinders normally characterize with failure mechanism wear and tear.Since the minimum working pressure increases with the number of working cycles,the minimum working pressure is chosen as degradation signal.PACE model is fundamentally composed of two operations：path classification and remaining useful life（RUL） estimation.Path classification is to classify a current degradation path as belonging to one or more of previously collected exemplary degradation paths.RUL estimation is to use the resulting memberships to estimate the remaining useful life.In order for verification and validation of PACE prognostic method,six pneumatic cylinders are tested.The test data is analyzed by PACE prognostics.It is found that the PACE based prognosis method has higher prediction accuracy and smaller variance and PACE model is significantly outperform population based prognostics especially for small specimen condition.PACE model based method solved the problem of prediction accuracy for small specimen pneumatic cylinders＇ prognosis.

Research on the Path to Creating Home Gardening Brand Assets Based on Customers——A Case Study of Hongyue Garden Maker

In this paper,using the research method of grounded theory,with the competitive brand of home gardening—Hongyue Garden Maker as the specific object of study,we collect the data through interviews and surveys,conduct coding analysis step by step on the data,establish the brand asset creation path model consisting of some main dimensions including " brand salience"," brand performance"," brand image"," brand judgment"," brand feeling",and " brand resonance",and reveal the interaction and logical relationship between the above dimensions,so as to provide theoretical support for the asset creation of many kinds of home gardening and other brands.

Broadband ground motion simulation using a hybrid approach of the May 21, 2021 M7.4 earthquake in Maduo, Qinghai, China

In this study,the broadband ground motions of the 2021 M7.4 Maduo earthquake were simulated to overcome the scarcity of ground motion recordings and the low resolution of macroseismic intensity map in sparsely populated high-altitude regions.The simulation was conducted with a hybrid methodology,combining a stochastic high-frequency simulation with a low-frequency ground motion simulation,from the regional 1-D velocity structure model and the Wang WM et al.(2022)source rupture model,respectively.We found that the three-component waveforms simulated for specific stations matched the waveforms recorded at those stations,in terms of amplitude,duration,and frequency content.The validation results demonstrate the ability of the hybrid simulation method to reproduce the main characteristics of the observed ground motions for the 2021 Maduo earthquake over a broad frequency range.Our simulations suggest that the official map of macroseismic intensity tends to overestimate shaking by one intensity unit.Comparisons of simulations with empirical ground motion models indicate generally good consistency between the simulated and empirically predicted intensity measures.The high-frequency components of ground motions were found to be more prominent,while the low-frequency components were not,which is unexpected for large earthquakes.Our simulations provide valuable insight into the effects of source complexity on the level and variability of the resulting ground motions.The acceleration and velocity time histories and corresponding response spectra were provided for selected representative sites where no records were available.The simulated results have important implications for evaluating the performance of engineering structures in the epicentral regions of this earthquake and for estimating seismic hazards in the Tibetan regions where no strong ground motion records are available for large earthquakes.

Metamorphic gradient modification in the Early Cretaceous Northern Andes subduction zone:A record from thermally overprinted high-pressure rocks

New field observations and petrological data from Early Cretaceous metamorphic rocks in the Central Cordillera of the Colombian Andes allowed the recognition of thermally overprinted high-pressure rocks derived from oceanic crust protoliths.The obtained metamorphic path suggests that the rocks evolved from blueschist to eclogite facies towards upper amphibolite to high-pressure granulite facies transitional conditions.Eclogite facies conditions,better recorded in mafic protoliths,are revealed by relic lawsonite and phengite,bleb-to worm-like diopside-albite symplectites,as well as garnet core composition.Upper amphibolite to high pressure granulite facies overprinting is supported by coarse-grained brown-colored Ti-rich amphibole,augite,and oligoclase recrystallization,as well as the record of partial melting leucosomes.Phase equilibria and pressure-temperature(P-T)path modeling suggest initial high-pressure metamorphic conditions M1 yielding 18.2-24.5 kbar and 465-580℃,followed by upper amphibolite to high pressure granulite facies overprinting stage M2 yielding 6.5-14.2 kbar and 580-720℃.Retrograde conditions M3 obtained through chlorite thermometry yield temperatures ranging around 286-400℃at pressures below 6.5-11 kbar.The obtained clockwise P-T path,the garnet zonation pattern revealing a decrease in X_(grs)/X_(prp)related to Mg#increment from core to rim,the presence of partial melting veins,as well as regional constraints,document the modification of the thermal structure of the active subduction zone in Northern Andes during the Early Cretaceous.Such increment of the metamorphic gradient within the subduction interface is associated with slab roll-back geodynamics where hot mantle inflow was triggered.This scenario is also argued by the reported trench-ward magmatic arc migration and multiple extensional basin formation during this period.The presented example constitutes the first report of Cretaceous roll-back-related metamorphism in the Caribbean and Andean realms,representing an additional piece of evidence for a margin-scale extensional event that modified the northwestern border of South America during the Early Cretaceous.

Methods for Reliability Assessment under Irregular Time-Varying-Stress Degradation Testing

Degradation tests are often used to assess the reliability of products with long failure-time or few test units. Much of the previous work on reliability assessment methods has focused on constant-stress degradation test( CSDT) and accelerated degradation test( ADT), mainly under the constant, step or progressive stresses. However,in actual testing environments,some stresses are difficult to control and vary with time irregularly,which are quite different from the three stresses mentioned above. In this paper a new approach was presented for reliability assessment with degradation data under irregular time-varying-stress( ITVS).Firstly,the conventional degradation path modeling method was improved by taking into account the influences of the variable stress on the degradation variable. Then,an example was conducted to show the effectiveness of our improved model.

Improved ant colony optimization algorithm for the traveling salesman problems

Ant colony optimization （ACO） is a new heuristic algo- rithm which has been proven a successful technique and applied to a number of combinatorial optimization problems. The traveling salesman problem （TSP） is among the most important combinato- rial problems. An ACO algorithm based on scout characteristic is proposed for solving the stagnation behavior and premature con- vergence problem of the basic ACO algorithm on TSP. The main idea is to partition artificial ants into two groups： scout ants and common ants. The common ants work according to the search manner of basic ant colony algorithm, but scout ants have some differences from common ants, they calculate each route＇s muta- tion probability of the current optimal solution using path evaluation model and search around the optimal solution according to the mutation probability. Simulation on TSP shows that the improved algorithm has high efficiency and robustness.

Life prediction and test period optimization research based on small sample reliability test of hydraulic pumps

Hydraulic pumps belong to reliable long-life hydraulic components. The reliability evaluation includes characters such as long test period,high cost,and high power loss and so on. Based on the principle of energy-saving and power recovery,a small sample hydraulic pump reliability test rig is built,and the service life of hydraulic pump is predicted,and then the sampling period of reliability test is optimized. On the basis of considering the performance degradation mechanism of hydraulic pump,the feature information of degradation distribution of hydraulic pump volumetric efficiency during the test is collected,so an optimal degradation path model of feature information is selected from the aspect of fitting accuracy,and pseudo life data are obtained. Then a small sample reliability test of period constrained optimization search strategy for hydraulic pump is constructed to solve the optimization problem of the test sampling period and tightening end threshold,and it is verified that the accuracy of the minimum sampling period by the non-parametric hypothes is tested. Simulation result shows it could possess instructional significance and referenced value for hydraulic pump reliability life evaluation and the test's research and design.

PRINCIPLES AND PARAMETER DESIGN FOR AC-DC THREE-DEGREE FREEDOM HYBRID MAGNETIC BEARINGS

To simplify the mechanical structure, decrease the overall system size of the 3-degree freedom axial-radial magnetic bearings and reduce the manufacturing costs as well as operating costs, an innovated AC-DC 3-degree freedom hybrid magnetic bearing is proposed, which is driven by a DC amplifier in axial direction and a 3-phase power converter in radial directions respectively, and the axial and radial bias magnetic fluxes are provided with a common radial polarized permanent magnet ring. The principle producing magnetic suspension forces is introduced. By using equivalent magnetic circuit method, the calculation formulas of magnetic suspension forces and the mathematics models of the system are deduced. Nonlinearities of suspension forces and cross coupling between different degree freedoms are studied further by calculating the suspension forces at different displacements and control currents to validate the feasibility of the mathematics model. Then based on the mathematics models of the bearing, a control method of this novel bearing is designed. Lastly, the methods on parameter design and calculations of the bearing are presented, and an applicable prototype is simulated to analyze the magnetic path by using finite element analysis. The theory analysis and simulation results have shown that this magnetic bearing incorporates the merits of 3-phase AC drive, permanent magnet flux biased and axial-radial combined control, and reduces overall system size and has higher efficiency and lower cost, This innovated magnetic bearing has a wide application in super-speed and super-precision numerical control machine tools, bearingless motors, high-speed flywheels, satellites, etc.

Analyzing Industrial Structure Evolution of Old Industrial Cities Using Evolutionary Resilience Theory：A Case Study in Shenyang of China

The recession and revitalization of old industrial cities concerns urban industrial evolution and its characteristics. Based on the theory of evolutionary resilience, we developed an analytical framework for the industrial structure evolution of old industrial cities, and applied the framework to a case study in Shenyang. The following conclusions are drawn. First, since 1978, Shenyang's industrial growth capacity has shown fluctuation between ‘contraction-expansion'. As the secondary industry has a much stronger expansionary and contractionary capacity for growth, this results in lacking stability leading to industrial structure transformation. Second, since 1999, the orientation towards a high-end manufacturing industry in Shenyang has weakened, and the evolution of the new and old growth path is characterized by low-end orientation. Third, since 2007, Shenyang's industrial innovation output capacity has dropped sharply which has been significantly affected by scientific and technological personnel and enterprise-owed science and technology institutions and to a less extent by R&D expenditure. We applied the resilience theory to study the industrial evolution of an old industrial city, explored new study perspectives on industrial evolution and verified the applicability of the resilience theory. This paper provides a scientific reference for understanding the recent deceleration in economic growth in the Northeast old industrial base, and for exploring new paths toward revitalization.

A routing and positioning algorithm based on a K-barrier for use in an underground wireless sensor network

Deployment of nodes based on K-barrier coverage in an underground wireless sensor network is described. The network has automatic routing recovery by using a basic information table (BIT) for each node. An RSSI positioning algorithm based on a path loss model in the coal mine is used to calculate the path loss in real time within the actual lane way environment. Simulation results show that the packet loss can be controlled to less than 15% by the routing recovery algorithm under special recovery circum- stances. The location precision is within 5 m, which greatly enhances performance compared to tradi- tional frequency location systems. This approach can meet the needs for accurate location underground.

Influence Factors Concept Model for Public Participation in Nanotechnology Risk Communication

Based on risk social cognition theory and planned behavior theory, the influence factors of the public participation in the nanotechnology risk communication are analyzed,and the concept model is presented to analyze their relationships and functional mechanism. In the model,the risk communication behaviors are divided into two variables of the public opinion expression and information acquisition,and the subjective norm divided into the internal and external social networks. Then the questionnaire is designed so as to verify the proposed model and analyze their relationships. The survey data are analyzed using SMART PLS software. The validity analysis shows that the questionnaire has a high convergence and discriminant validity. In addition, the Cronbach'a coefficient of each item is more than 0. 70,which shows the questionnaire has a high credibility. Based on the statistical data analysis, relationships of the influence factors are obtained.Further,the influence path model of the public attitude,intention,self regulation and behavior control in the risk communication is established. According to the Bootstrap algorithm in SMART,the path coefficient and its explanation variance of each influence factor are obtained. The calculation results show that the explanation variance values are all bigger than 10% and the path is reliable.Based on the path model, the influence path and function relationships of the participation attitude, subjective norm and behavior control on the participation intention and behavior are obtained. This will provide theoretical and data supports for the risk management and strategy making of the public participation in nanotechnology risk communication.

A Study of Propagation in Shenzhen City

Surveying the propagation path loss behavior of Shenzhen city and from the data recorded we can obtain the city’s path loss slopes, which can be comparatively regarded as the reliable bases of system design.

Multivariate statistical and bioinformatic analyses for the seasonal variations of actinobacterial community structures in a drinking water reservoir

Actinobacterial community is a conspicuous part of aquatic ecosystems and displays an important role in the case of biogeochemical cycle,but little is known about the seasonal variation of actinobacterial community in reservoir ecological environment.In this study,the high-throughput techniques were used to investigate the structure of the aquatic actinobacterial community and its inducing water quality parameters in different seasons.The results showed that the highest diversity and abundance of actinobacterial community occurred in winter,with Sporichthya(45.42%)being the most abundant genus and Rhodococcus sp.(29.32%)being the most abundant species.Network analysis and correlation analysis suggested that in autumn the dynamics of actinobacterial community were infuenced by more factors and Nocardioides sp.SX2R5S2 was the potential keystone species which was negatively correlated with temperature(R=-0.72,P<0.05).Changes in environmental factors could significantly affect the changes in actinobacterial community,and the dynamics of temperature,dissolved oxygen(DO),and turbidity are potential conspicuous factors infuencing seasonal actinobacterial community trends.The partial least squares path modeling further elucidated that the combined effects of DO and temperature not only in the diversity of actinobacterial community but also in other water qualities,while the physiochemical parameters(path coefficient=1.571,P<0.05)was strong environmental factors in natural mixture period.These results strengthen our understanding of the dynamics and structures of actinobacterial community in the drinking water reservoirs and provide scientific guidance for further water quality management and protection in water sources.

Analyses of maximum-speed path definition at single-lane roundabouts

The process of designing roundabouts is an iterative process through which, in several checks, the design elements of a roundabout get optimized. Existing regulations for roundabouts involve swept path analyses, sight distance analyses and speed analyses of vehicles passing through the roundabout. Speed analyses are done mostly based on two models, Dutch and American. Each of these two models, in their own way takes into account design elements of the roundabouts, and the US model also envisions the construction of vehicle paths through the roundabout. Main assumption of both models is that vehicle paths through roundabouts consist of few connected radii. US models for path definition takes into account safety distances from marked lines and geometric elements（curbs） at the entrance and exit and through roundabout. Experimentally determined elements of the vehicle path through the roundabout, do not correspond to those recommendations. Comparison of the measured speed at the roundabouts and speed calculated according to aforementioned models at several roundabouts in Croatia, showed a significant difference. An experimental research was conducted as a first step in developing a new model for operating speed through roundabouts. The research aimed to define the basic path elements of vehicle movement in the roundabout at which the maximum speed is achieved. Results of the study are presented in this paper.

PATH PROBLEM SIMPLIFICATION WITH DESIRED BOUNDED LENGTHS IN ACYCLIC NETWORKS

Path determination is a fundamental problem of operations research. Current solutions mainly focus on the shortest and longest paths. We consider a more generalized problem; specifically, we consider the path problem with desired bounded lengths （DBL path problem）. This problem has extensive applications; however, this problem is much harder, especially for large-scale problems. An effective approach to this problem is equivalent simplification. We focus on simplifying the problem in acyclic networks and creating a path length model that simplifies relationships between various path lengths. Based on this model, we design polynomial algorithms to compute the shortest, longest, second shortest, and second longest paths that traverse any arc. Furthermore, we design a polynomial algorithm for the equivalent simplification of the is O（m）, where m is the number of arcs. DBL path problem. The complexity of the algorithm

On the effects of spatial resolution on effective distance measurement in digital landscapes

Background:Connectivity is an important landscape attribute in ecological studies and conservation practices and is often expressed in terms of effective distance.If the cost of movement of an organism over a landscape is effectively represented by a raster surface,effective distances can be equated with the cost-weighted distance of least-cost paths.It is generally recognized that this measure is sensitive to the grid’s cell size,but little is known if it is always sensitive in the same way and to the same degree and if not,what makes it more(or less)sensitive.We conducted computational experiments with both synthetic and real landscape data,in which we generated and analyzed large samples of effective distances measured on cost surfaces of varying cell sizes derived from those data.The particular focus was on the statistical behavior of the ratio—referred to as‘accuracy indicator’—of the effective distance measured on a lower-resolution cost surface to that measured on a higher-resolution cost surface.Results:In the experiment with synthetic cost surfaces,the sample values of the accuracy indicator were generally clustered around 1,but slightly greater with the absence of linear sequences(or barriers)of high-cost or inadmissible cells and smaller with the presence of such sequences.The latter tendency was more dominant,and both tendencies became more pronounced as the difference between the spatial resolutions of the associated cost surfaces increased.When two real satellite images(of different resolutions with fairly large discrepancies)were used as the basis of cost estimation,the variation of the accuracy indicator was found to be substantially large in the vicinity(1500 m)of the source but decreases quickly with an increase in distance from it.Conclusions:Effective distances measured on lower-resolution cost surfaces are generally highly correlated with—and useful predictors of—effective distances measured on higher-resolution cost surfaces.This relationship tends to be weakened when linear barriers to dispersal(e.g.,roads and rivers)exist,but strengthened when moving away from sources of dispersal and/or when linear barriers(if any)are detected by other presumably more accessible and affordable sources such as vector line data.Thus,if benefits of high-resolution data are not likely to substantially outweigh their costs,the use of lower resolution data is worth considering as a cost-effective alternative in the application of least-cost path modeling to landscape connectivity analysis.

Interference of human's ankle to the channel characteristics of near surface WUSN

Because of its potential applications in agriculture, environment monitoring and so on, wireless underground sensor network（WUSN） has been researched more and more extensively in recent years. The main and most important difference of WUSN to terrestrial wireless sensor network（WSN） is the channel characteristics, which determines the design methodology of it. In this paper, the propagation character of electromagnetic（EM） wave in the near surface WUSN is analyzed, as well as the path loss model of it is given. In addition, the influence of human＇s ankle to the channel characteristics of near surface WUSN is investigated by electromagnetic theory analysis, simulation and experiment. A novel path loss model of near surface WUSN which takes the interference of human＇s ankle into consideration is proposed. It is verified that the existing of human above the WUSN system may cause additional attenuation to the signal of near surface WUSN which propagates as lateral wave along the ground. Moreover, the relation of the attenuation and operating frequency is deduced, which gives a reference to extend the frequency band applied in WUSN.