Designing a new robust on-line secondary path modeling technique for feedforward active noise control systems

Several approaches have been introduced in the literature for active noise control (ANC) systems. Since the filtered-x least-mean-square (FxLMS) algorithm appears to be the best choice as a controller filter, researchers tend to improve performance of ANC systems by enhancing and modifying this algorithm. This paper proposes a new version of the FxLMS algorithm, as a first novelty. In many ANC applications, an on-line secondary path modeling method using white noise as a training signal is required to ensure convergence of the system. As a second novelty, this paper proposes a new approach for on-line secondary path modeling on the basis of a new variable-step-size (VSS) LMS algorithm in feed forward ANC systems. The proposed algorithm is designed so that the noise injection is stopped at the optimum point when the modeling accuracy is sufficient. In this approach, a sudden change in the secondary path during operation makes the algorithm reactivate injection of the white noise to re-adjust the secondary path estimate. Comparative simulation results shown in this paper indicate the effectiveness of the proposed approach in reducing both narrow-band and broad-band noise. In addition, the proposed ANC system is robust against sudden changes of the secondary path model.

An efficient online secondary path estimation for feedback active noise control systems

In practical cases for active noise control (ANC), the secondary path has usually a time varying behavior. For these cases, an online secondary path modeling method that uses a white noise as a training signal is required to ensure convergence of the system. The modeling accuracy and the convergence rate are increased when a white noise with a larger variance is used. However, the larger variance increases the residual noise, which decreases performance of the system and additionally causes instability problem to feedback structures. A sudden change in the secondary path leads to divergence of the online secondary path modeling filter. To overcome these problems, this paper proposes a new approach for online secondary path modeling in feedback ANC systems. The proposed algorithm uses the advantages of white noise with larger variance to model the secondary path, but the injection is stopped at the optimum point to increase performance of the algorithm and to prevent the instability effect of the white noise. In this approach, instead of continuous injection of the white noise, a sudden change in secondary path during the operation makes the algorithm to reactivate injection of the white noise to correct the secondary path estimation. In addition, the proposed method models the secondary path without the need of using off-line estimation of the secondary path. Considering the above features increases the convergence rate and modeling accuracy, which results in a high system performance. Computer simulation results shown in this paper indicate effectiveness of the proposed method.

A variable step-size FxLMS algorithm for feedforward active noise control systems based on a new online secondary path modelling technique

Several approaches have been introduced in literature for active noise control (ANC) systems. Since FxLMS algorithm appears to be the best choice as a controller filter, researchers tend to improve performance of ANC systems by enhancing and modifying this algorithm. This paper proposes a new version of FxLMS algorithm. In many ANC applications an online secondary path modelling method using a white noise as a training signal is required to ensure convergence of the system. This paper also proposes a new approach for online secondary path modelling in feedfoward ANC systems. The proposed algorithm stops injection of the white noise at the optimum point and reactivate the injection during the operation, if needed, to maintain performance of the system. Benefiting new version of FxLMS algorithm and not continually injection of white noise makes the system more desirable and improves the noise attenuation performance. Comparative simulation results indicate effectiveness of the proposed approach.

A new online secondary path modelling method for feedforward active noise control systems

An online secondary path modelling method using a white noise as a training signal is required in many applications of active noise control (ANC) to ensure convergence of the system. Not continually injection of white noise during system operation makes the system more desirable. The purposes of the proposed method are two folds: controlling white noise by preventing continually injection, and benefiting white noise with a larger variance. The modelling accuracy and the convergence rate increase when a white noise with larger variance is used, however larger the variance increases the residual noise, which decreases performance of the system. This paper proposes a new approach for online secondary path modelling in feedfoward ANC systems. The proposed algorithm uses the advantages of the white noise with larger variance to model the secondary path, but the injection is stopped at the optimum point to increase performance of the system. Comparative simulation results shown in this paper indicate effectiveness of the proposed approach in controlling active noise.

An optimized online secondary path modeling method for single-channel feedback ANC systems

This paper proposes a new method for online secondary path modeling in feedback active noise control (ANC) systems. In practical cases, the secondary path is usually time varying. For these cases, online modeling of secondary path is required to ensure convergence of the system. In literature the secondary path estimation is usually performed offline, prior to online modeling, where in the proposed system there is no need for using offline estimation. The proposed method consists of two steps: a noise controller which is based on an FxLMS algorithm, and a variable step size (VSS) LMS algorithm which is used to adapt the modeling filter with the secondary path. In order to increase performance of the algorithm in a faster convergence and accurate performance, we stop the VSS-LMS algorithm at the optimum point. The results of computer simulation shown in this paper indicate effectiveness of the proposed method.

Study on dynamic system optimum assignment to establish marginal time equilibrium

Several analytical methods for Dynamic System Optimum (DSO) assignment have been proposed but they are basically classified into two kinds. This chapter attempts to establish DSO by equilbrating the path dynamic marginal time (DMT). The authors analyze the path DMT for a single path with tandem bottlenecks and showed that the path DMT is not the simple summation of DMT associated with each bottleneck along the path. Next, the authors examined the DMT of several paths passing through a common bottleneck. It is shown that the externality at the bottleneck is shared by the paths in proportion to their demand from the current time until the queue vanishes. This share of the externality is caused by the departure rate shift under first in first out (FIFO) and the externality propagates to the downstream bottlenecks. However, the externalities propagates to the downstream are calculated out if downstream bottlenecks exist. Therefore, the authors concluded that the path DMT can be evaluated without considering the propagation of the externalities, but just as in the evaluation of the path DMT for a single path passing through a series of bottlenecks between the origin and destination. Based on the DMT analysis, the authors finally proposed a heuristic solution algorithm and verified it by comparing the numerical solution with the analytical one.

Practical path planning and obstacle avoidance for autonomous mowing

There is a need for systems which can autonomously perform coverage tasks on large outdoor areas. Unfortunately, the state-of-the-art is to use GPS based localization, which is not suitable for precise operations near trees and other obstructions. In this paper we present a robotic platform for autonomous coverage tasks. The system architecture integrates laser based localization and mapping using the Atlas Framework with Rapidly-Exploring Random Trees path planning and Virtual Force Field obstacle avoidance. We demonstrate the performance of the system in simulation as well as with real world experiments.

Effects of recreational use and fragmentation on the understorey vegetation and soil microbial communities of urban forests in southern Finland

The impacts of fragmentation and recreational use on the hemiboreal urban forest understorey vegetation and the microbial community of the humus layer (the phospholipid fatty acid (PLFA) pattern, microbial biomass and microbial activity, measured as basal respiration) were examined in the greater Helsinki area, southern Finland. Trampling tolerance of 1) herb-rich OMT, 2) mesic MT, and 3) sub-xeric VT forests (in decreasing order of fertility) was studied by comparing relative understorey vegetation cover (urban/untrampled reference ratio) of the three forest types. The trampling tolerance of forest vegetation increased with the productivity of the site (sub-xeric < mesic < herb-rich). Wear of understorey vegetation correlated positively with the number of residents (i.e., recreational pressure) around the forest patch. An increase of 15000 residents within a radius of 1 km around a forest patch was associated with ca. 30% decrease in the relative understorey vegetation cover. The cover of dwarf shrub Vaccinium myrtillus in particular decreased with increasing levels of wear. The cover of mosses in urban forests was less than half of that in untrampled reference areas. Cover of tree saplings, mainly Sorbus aucuparia, and some resilient herbs was higher than in the reference areas. In small urban forest fragments, broad-leaved trees, grasses and herbs were more abundant and mosses were scarcer than in larger urban forest areas. Thus, due to trampling and edge effects, resilient herb and grass species are replacing sensitive dwarf shrubs, mosses and lichens in urban forests. Differences in the soil microbial community structure were found between paths and untrampled areas and the effects of paths extended more than one meter from the paths. Paths supported approximately 25-30% higher microbial biomass with a transition zone of at least 1 m from the path edge. However, microbial activity per unit of biomass was lower on paths than in untrampled areas. Furthermore, microbial biomass and activity were 30-45% lower at the first 20 m into the forest fragments, due to low moisture content of humus near the edge. The decreased microbial activity detected at forest edges and paths implies decreased litter decomposition rates, and thus, a change in nutrient cycling. Changes in the decomposition and nutrient supply may in turn affect the diversity and function of plant communities in urban forests. Keywords: boreal forest vegetation, edge effects, phospholipid fatty acids, trampling, urban woodlands, wear

The effects of habitat edges and trampling intensity on vegetation in urban forests

Although changes in urban forest vegetation have been documented in previous Finnish studies, the reasons for these changes have not been studied explicitly. Especially, the consequences of forest fragmentation, i.e. the fact that forest edges receive more solar radiation, wind and air-borne nutrients than interiors have been ignored. In order to limit the change in urban forest vegetation we need to know why it occurs. Therefore, the effects of edges and recreational use of urban forests on vegetation were investigated together in this thesis to reveal the relative strengths of these effects and to provide recommendations for forest management. Data were collected in the greater Helsinki area (in the cities of Helsinki, Vantaa and Espoo, and in the municipalities of Sipoo and Tuusula) and in the Lahti region (in the city of Lahti and in the municipality of Hollola) by means of systematic and randomized vegetation and soil sampling and tree measurements. Sample plots were placed from the forest edges to the interiors to investigate the effects of forest edges, and on paths of different levels of wear and off these paths to investigate the effects of trampling. The natural vegetation of mesic and sub-xeric forest site types studied was sensitive both to the effects of the edge and to trampling. The abundances of dwarf shrubs and bryophytes decreased, while light- and nitrogen-demanding herbs and grasses - and especially Sorbus aucuparia – were favoured at the edges and next to the paths. Results indicated that typical forest site types at the edges are changing toward more nitrophilic vegetation communities. Covers of the most abundant forest species decreased considerably – even tens of percentages – from interiors to the edges indicating strong edge effects. These effects penetrated at least up to 50 m from the forest edges into the interiors, especially at south to west facing open edges. The effects of trampling were pronounced on paths and even low levels of trampling decreased the abundances of certain species considerably. The effects of trampling extended up to 8 m from path edges. Results showed that the fragmentation of urban forest remnants into small and narrow patches should be avoided in order to maintain natural forest understorey vegetation in the urban setting. Thus, urban forest fragments left within urban development should be at least 3 ha in size, and as circular as possible. Where the preservation of representative original forest interior vegetation is a management aim, closed edges with conifers can act as an effective barrier against solar radiation, wind and urban load, thereby restricting the effects of the edge. Tree volume at the edge should be at least 225-250 m3 ha-1 and the proportion of conifers (especially spruce) 80% or more of the tree species composition. Closed, spruce-dominated edges may also prevent the excessive growth of S. aucuparia saplings at urban forest edges. In addition, closed edges may guide people’s movements to the maintained paths, thus preventing the spontaneous creation of dense path networks. In urban areas the effects of edges and trampling on biodiversity may be considerable, and are important to consider when the aim of management is to prevent the development of homogeneous herb-grass dominated vegetation communities, as was observed at the investigated edges.

Optimum atomic spacing for AlAs etching in GaAs epitaxial lift-off technology

With respect to GaAs epitaxial lift-off technology, we report here the optimum atomic spacing (5-10 nm) needed to etch off the AlAs release layer that is sandwiched between two GaAs epitaxial layers. The AlAs etching rate in hydrofluoric acid based solutions was monitored as a function of release layer thickness. We found a sudden quenching in the etching rate, approximately 20 times that of the peak value, at lower dimensions (similar to2.5 nm) of the AlAs epitaxial layer. Since this cannot be explained on the basis of a previous theory (inverse square root of release layer thickness), we propose a diffusion-limited mechanism to explain this reaction process. With the diffusion constant being a mean-free-path-dependent parameter, a relation between the mean free path and the width of the channel is considered. This relation is in reasonable agreement with the experimental results and gives a good physical insight to the reaction kinetics.

Estimation of cutting volume with three inventory methods for harvest planning in Canadian boreal forests.

Two methods of pre-harvest inventory were designed and tested on three cutting sites containing a total of 197 500 m3 of wood. These sites were located on flat-ground boreal forests located in northwestern Quebec. Both methods studied involved scaling of trees harvested to clear the road path one year (or more) prior to harvest of adjacent cut-blocks. The first method (ROAD) considers the total road right-of-way volume divided by the total road area cleared. The resulting volume per hectare is then multiplied by the total cut-block area scheduled for harvest during the following year to obtain the total estimated cutting volume. The second method (STRATIFIED) also involves scaling of trees cleared from the road. However, in STRATIFIED, log scaling data are stratified by forest stand location. A volume per hectare is calculated for each stretch of road that crosses a single forest stand. This volume per hectare is then multiplied by the remaining area of the same forest stand scheduled for harvest one year later. The sum of all resulting estimated volumes per stand gives the total estimated cutting-volume for all cut-blocks adjacent to the studied road. A third method (MNR) was also used to estimate cut-volumes of the sites studied. This method represents the actual existing technique for estimating cutting volume in the province of Quebec. It involves summing the cut volume for all forest stands. The cut volume is estimated by multiplying the area of each stand by its estimated volume per hectare obtained from standard stock tables provided by the governement. The resulting total estimated volume per cut-block for all three methods was then compared with the actual measured cut-block volume (MEASURED). This analysis revealed a significant difference between MEASURED and MNR methods with the MNR volume estimate being 30 % higher than MEASURED. However, no significant difference from MEASURED was observed for volume estimates for the ROAD and STRATIFIED methods which respectively had estimated cutting volumes 19 % and 5 % lower than MEASURED. Thus the ROAD and STRATIFIED methods are good ways to estimate cut-block volumes after road right-of-way harvest for conditions similar to those examined in this study.

Influence of Training Set Selection in Artificial Neural Network-Based Propagation Path Loss Predictions

This paper analyzes the use of artificial neural networks (ANNs) for predicting the received power/path loss in both outdoor and indoor links. The approach followed has been a combined use of ANNs and ray-tracing, the latter allowing the identification and parameterization of the so-called dominant path. A complete description of the process for creating and training an ANN-based model is presented with special emphasis on the training process. More specifically, we will be discussing various techniques to arrive at valid predictions focusing on an optimum selection of the training set. A quantitative analysis based on results from two narrowband measurement campaigns, one outdoors and the other indoors, is also presented.

Growth window and possible mechanism of millimeter-thick single-walled carbon nanotube forests.

Our group recently reproduced the water-assisted growth method, so-called "SuperGrowth", of millimeter-thick single-walled carbon nanotube (SWNT) forests by using C2H4/H2/H2O/Ar reactant gas and Fe/Al2O3, catalyst. In this current work, a parametric study was carried out on both reaction and catalyst conditions. Results revealed that a thin Fe catalyst layer (about 0.5 nm) yielded rapid growth of SWNTs only when supported on Al2O3, and that Al2O3 support enhanced the activity of Fe, Co, and Ni catalysts. The growth window for the rapid SWNT growth was narrow, however. Optimum amount of added H2O increased the SWNT growth rate but further addition of H2O degraded both the SWNT growth rate and quality. Addition of H2 was also essential for rapid SWNT growth, but again, further addition decreased both the SWNT growth rate and quality. Because Al2O3 catalyzes hydrocarbon reforming, Al2O3 support possibly enhances the SWNT growth rate by supplying the carbon source to the catalyst nanoparticles. The origin of the narrow window for rapid SWNT growth is also discussed.

Understanding the synthesis of directly spinnable carbon nanotube forests

Carbon nanotube forests that can be spun directly from the growth substrate into pure, highly aligned webs, ribbons or yarn promise novel applications that capture the strength and other characteristics of this material. The precise conditions for high spinnability over a maximum proportion of the reactor space are extremely sensitive. The roles of catalyst, substrate, temperature, gas flow rates, reaction time with acetylene etc. were studied to identify and understand the key parameters and develop a robust, scalable process. Using a 44 mm (id) reactor, the optimum values for these variables were determined as comprising a 2.3 nm thick iron catalyst layer on a silicon substrate with 50 nm of thermal oxide; 670 °C running temperature; 650 sccm helium and 34 sccm acetylene for 20 min. The effects of deviating from these optima were explored and the role of amorphous carbon deposition clarified. Crown Copyright © 2009.

An algorithm to median shortest path problem (MSPP) in the design of urban transportation networks

This paper proposes an efficient solution algorithm for realistic multi-objective median shortest path problems in the design of urban transportation networks. The proposed problem formulation and solution algorithm to median shortest path problem is based on three realistic objectives via route cost or investment cost, overall travel time of the entire network and total toll revenue. The proposed solution approach to the problem is based on the heuristic labeling and exhaustive search technique in criteria space and solution space of the algorithm respectively. The first labels each node in terms of route cost and deletes cyclic and infeasible paths in criteria space imposing cyclic break and route cost constraint respectively. The latter deletes dominated paths in terms of objectives vector in solution space in order to identify a set of Pareto optimal paths. The approach, thus, proposes a non-inferior solution set of Pareto optimal paths based on non-dominated objective vector and leaves the ultimate decision to decision-makers for purpose specific final decision during applications. A numerical experiment is conducted to test the proposed algorithm using artificial transportation network. Sensitivity analyses have shown that the proposed algorithm is advantageous and efficient over existing algorithms to find a set of Pareto optimal paths to median shortest paths problems.