Integrating object locations in the memory representation of a spatial layout

The present study investigated how object locations learned separately are integrated and represented as a single spatial layout in memory. Two experiments were conducted in which participants learned a room-sized spatial layout that was divided into two sets of five objects. Results suggested that integration across sets was performed efficiently when it was done during initial encoding of the environment but entailed cost in accuracy when it was attempted at the time of memory retrieval. These findings suggest that, once formed, spatial representations in memory generally remain independent and integrating them into a single representation requires additional cognitive processes.

Modeling kinect sensor noise for improved 3D reconstruction and tracking

We contribute an empirically derived noise model for the Kinect sensor. We systematically measure both lateral and axial noise distributions, as a function of both distance and angle of the Kinect to an observed surface. The derived noise model can be used to filter Kinect depth maps for a variety of applications. Our second contribution applies our derived noise model to the KinectFusion system to extend filtering, volumetric fusion, and pose estimation within the pipeline. Qualitative results show our method allows reconstruction of finer details and the ability to reconstruct smaller objects and thinner surfaces. Quantitative results also show our method improves pose estimation accuracy. © 2012 IEEE.

Localization and place recognition using an ultra-wide band (UWB) radar

This paper presents an approach to mobile robot localization, place recognition and loop closure using a monostatic ultra-wide band (UWB) radar system. The UWB radar is a time-of-flight based range measurement sensor that transmits short pulses and receives reflected waves from objects in the environment. The main idea of the poposed localization method is to treat the received waveform as a signature of place. The resulting echo waveform is very complex and highly depends on the position of the sensor with respect to surrounding objects. On the other hand, the sensor receives similar waveforms from the same positions.Moreover, the directional characteristics of dipole antenna is almost omnidirectional. Therefore, we can localize the sensor position to find similar waveform from waveform database. This paper proposes a place recognitionmethod based on waveform matching, presents a number of experiments that illustrate the high positon estimation accuracy of our UWB radar-based localization system, and shows the resulting loop detection performance in a typical indoor office environment and a forest.

Analyzing multi-fiber reconstruction in high angular resolution diffusion imaging using the tensor distribution function

High-angular resolution diffusion imaging (HARDI) can reconstruct fiber pathways in the brain with extraordinary detail, identifying anatomical features and connections not seen with conventional MRI. HARDI overcomes several limitations of standard diffusion tensor imaging, which fails to model diffusion correctly in regions where fibers cross or mix. As HARDI can accurately resolve sharp signal peaks in angular space where fibers cross, we studied how many gradients are required in practice to compute accurate orientation density functions, to better understand the tradeoff between longer scanning times and more angular precision. We computed orientation density functions analytically from tensor distribution functions (TDFs) which model the HARDI signal at each point as a unit-mass probability density on the 6D manifold of symmetric positive definite tensors. In simulated two-fiber systems with varying Rician noise, we assessed how many diffusionsensitized gradients were sufficient to (1) accurately resolve the diffusion profile, and (2) measure the exponential isotropy (EI), a TDF-derived measure of fiber integrity that exploits the full multidirectional HARDI signal. At lower SNR, the reconstruction accuracy, measured using the Kullback-Leibler divergence, rapidly increased with additional gradients, and EI estimation accuracy plateaued at around 70 gradients.

Estimating winter crop area across seasons and regions using time-sequential MODIS imagery.

The wheat grain industry is Australia's second largest agricultural export commodity. There is an increasing demand for accurate, objective and near real-time crop production information by industry. The advent of the Moderate Resolution Imaging Spectroradiometer (MODIS) satellite platform has augmented the capability of satellite-based applications to capture reflectance over large areas at acceptable pixel scale, cost and accuracy. The use of multi-temporal MODIS-enhanced vegetation index (EVI) imagery to determine crop area was investigated in this article. Here the rigour of the harmonic analysis of time-series (HANTS) and early-season metric approaches was assessed when extrapolating over the entire Queensland (QLD) cropping region for the 2005 and 2006 seasons. Early-season crop area estimates, at least 4 months before harvest, produced high accuracy at pixel and regional scales with percent errors of -8.6% and -26% for the 2005 and 2006 seasons, respectively. In discriminating among crops at pixel and regional scale, the HANTS approach showed high accuracy. The errors for specific area estimates for wheat, barley and chickpea were 9.9%, -5.2% and 10.9% (for 2005) and -2.8%, -78% and 64% (for 2006), respectively. Area estimates of total winter crop, wheat, barley and chickpea resulted in coefficient of determination (R(2)) values of 0.92, 0.89, 0.82 and 0.52, when contrasted against the actual shire-scale data. A significantly high coefficient of determination (0.87) was achieved for total winter crop area estimates in August across all shires for the 2006 season. Furthermore, the HANTS approach showed high accuracy in discriminating cropping area from non-cropping area and highlighted the need for accurate and up-to-date land use maps. The extrapolability of these approaches to determine total and specific winter crop area estimates, well before flowering, showed good utility across larger areas and seasons. Hence, it is envisaged that this technology might be transferable to different regions across Australia.

Numerical studies on quasilinear and linear elliptic equations

We explore here the acceleration of convergence of iterative methods for the solution of a class of quasilinear and linear algebraic equations. The specific systems are the finite difference form of the Navier-Stokes equations and the energy equation for recirculating flows. The acceleration procedures considered are: the successive over relaxation scheme; several implicit methods; and a second-order procedure. A new implicit method—the alternating direction line iterative method—is proposed in this paper. The method combines the advantages of the line successive over relaxation and alternating direction implicit methods. The various methods are tested for their computational economy and accuracy on a typical recirculating flow situation. The numerical experiments show that the alternating direction line iterative method is the most economical method of solving the Navier-Stokes equations for all Reynolds numbers in the laminar regime. The usual ADI method is shown to be not so attractive for large Reynolds numbers because of the loss of diagonal dominance. This loss can however be restored by a suitable choice of the relaxation parameter, but at the cost of accuracy. The accuracy of the new procedure is comparable to that of the well-tested successive overrelaxation method and to the available results in the literature. The second-order procedure turns out to be the most efficient method for the solution of the linear energy equation.

A note on fractal dimensions of biomedical waveforms

In this paper, we study performance of Katz method of computing fractal dimension of waveforms, and its estimation accuracy is compared with Higuchi's method. The study is performed on four synthetic parametric fractal waveforms for which true fractal dimensions can be calculated, and real sleep electroencephalogram. The dependence of Katz's fractal dimension on amplitude, frequency and sampling frequency of waveforms is noted. Even though the Higuchi's method has given more accurate estimation of fractal dimensions, the study suggests that the results of Katz's based fractal dimension analysis of biomedical waveforms have to be carefully interpreted.

Quantifying Time Awake Posturographically

This thesis focuses on the issue of testing sleepiness quantitatively. The issue is relevant to policymakers concerned with traffic- and occupational safety; such testing provides a tool for safety legislation and -surveillance. The findings of this thesis provide guidelines for a posturographic sleepiness tester. Sleepiness ensuing from staying awake merely 17 h impairs our performance as much as the legally proscribed blood alcohol concentration 0.5 does. Hence, sleepiness is a major risk factor in transportation and occupational accidents. The lack of convenient, commercial sleepiness tests precludes testing impending sleepiness levels contrary to simply breath testing for alcohol intoxication. Posturography is a potential sleepiness test, since clinical diurnal balance testing suggests the hypothesis that time awake could be posturographically estimable. Relying on this hypothesis this thesis examines posturographic sleepiness testing for instrumentation purposes. Empirical results from 63 subjects for whom we tested balance with a force platform during wakefulness for maximum 36 h show that sustained wakefulness impairs balance. The results show that time awake is posturographically estimable with 88% accuracy and 97% precision which validates our hypothesis. Results also show that balance scores tested at 13:30 hours serve as a threshold to detect excessive sleepiness. Analytical results show that the test length has a marked effect on estimation accuracy: 18 s tests suffice to identify sleepiness related balance changes, but trades off some of the accuracy achieved with 30 s tests. The procedure to estimate time awake relies on equating the subject s test score to a reference table (comprising balance scores tested during sustained wakefulness, regressed against time awake). Empirical results showed that sustained wakefulness explains 60% of the diurnal balance variations, whereas the time of day explains 40% of the balance variations. The latter fact implies that time awake estimations also must rely on knowing the local times of both test and reference scores.

Jätteenkeräyksen ja -siirron yhteiskunnalliset kustannukset Punavuoressa – Tarkastelussa seka-, bio-, kartonki- ja paperijäte

Tämän pro gradu -tutkielman tarkoituksena on määrittää jätteenkeräyksen ja -siirron yhteiskunnalliset kustannukset valitulla tutkimusalueella Helsingin Punavuoressa. Jätteenkeräyksen ja -siirron kustannukset vastaavat suuruudeltaan merkittävää osaa jätehuollon kokonaiskustannuksista, minkä vuoksi kustannusten tutkimiselle ja tarkastelulle löytyy kysyntää. Lisäksi keräyksen ja siirron kustannukset saattavat vaihdella suuresti johtuen erilaisista kaupunkirakenteista,keräysmenetelmistä ja teknologioista, joten tapaustarkastelun avulla pystytään selvittämään yksityiskohtaisesti alueen jätteenkeräyksen ja -siirron kustannukset. Tutkimusalue Helsingin Punavuoressa on yksi Suomen tiheimmin asutuista alueista, missä jätteidenkeräystä hankaloittaa kapeat kadut, useat sisäpihoille sijoitetut jätehuoneet ja vilkas liikenne. Erityispiirteidensä vuoksi jätteenkeräys- ja siirto aiheuttaa tutkimusalueella yksityisten kustannusten lisäksi myös useita ulkoisvaikutuksia muun muassa ilmansaasteiden ja viihtyvyyshaittojen muodossa. Tässä työssä lasketaan jätteenkeräyksen ja -siirron yhteiskunnalliset kustannukset neljän eri jätelajin osalta huomioimalla sekä yksityiset kustannustekijät että ulkoiskustannuksina syntyvien päästöjen kustannukset. Työn aineistona on käytetty erilaisia kustannuslaskelmien kirjallisuuslähteitä, asiantuntija-arvioita ja tutkimusalueella tehtyjä kellotusmittauksia. Alueen kellotusmittauksiin perustuvalla aikaperusteisella laskentatavalla jätteenkeräyksen ja -siirron jätetonnikohtaisiksi keskimääräisiksi kustannuksiksi saatiin 73 €/t. Kustannuksissa havaittiin kuitenkin suuria jätelajikohtaisia eroja, jolloin keräyksen ja siirron kustannukset heittelivät 49–125 €/t välillä. Suuret jätelajikohtaiset kustannuserot ovat selitettävissä pitkälti jätteiden koostumuksella, koska kevyiden ja paljon tilaa vievien jätelajien jätetonnikohtaiset kustannukset olivat suurimpia. Teoriataustan ja lähdeaineiston perusteella saadut tulokset myös osoittavat, että jätteenkeräyksen ja siirron kustannuksista huomioitujen ulkoiskustannusten osuus on häviävän pieni verrattuna yksityisten kustannusten tasoon.

Computing Fractal Dimension of Signals using Multiresolution Box-counting Method

In this paper, we have developed a method to compute fractal dimension (FD) of discrete time signals, in the time domain, by modifying the box-counting method. The size of the box is dependent on the sampling frequency of the signal. The number of boxes required to completely cover the signal are obtained at multiple time resolutions. The time resolutions are made coarse by decimating the signal. The loglog plot of total number of boxes required to cover the curve versus size of the box used appears to be a straight line, whose slope is taken as an estimate of FD of the signal. The results are provided to demonstrate the performance of the proposed method using parametric fractal signals. The estimation accuracy of the method is compared with that of Katz, Sevcik, and Higuchi methods. In ddition, some properties of the FD are discussed.

Iterated stochastic filters with additive updates for dynamic system identification: Annealing-type iterations and the filter bank

A nonlinear stochastic filtering scheme based on a Gaussian sum representation of the filtering density and an annealing-type iterative update, which is additive and uses an artificial diffusion parameter, is proposed. The additive nature of the update relieves the problem of weight collapse often encountered with filters employing weighted particle based empirical approximation to the filtering density. The proposed Monte Carlo filter bank conforms in structure to the parent nonlinear filtering (Kushner-Stratonovich) equation and possesses excellent mixing properties enabling adequate exploration of the phase space of the state vector. The performance of the filter bank, presently assessed against a few carefully chosen numerical examples, provide ample evidence of its remarkable performance in terms of filter convergence and estimation accuracy vis-a-vis most other competing filters especially in higher dimensional dynamic system identification problems including cases that may demand estimating relatively minor variations in the parameter values from their reference states. (C) 2014 Elsevier Ltd. All rights reserved.

Streaming covariance selection with applications to adaptive querying in sensor networks

Sensor networks can be naturally represented as graphical models, where the edge set encodes the presence of sparsity in the correlation structure between sensors. Such graphical representations can be valuable for information mining purposes as well as for optimizing bandwidth and battery usage with minimal loss of estimation accuracy. We use a computationally efficient technique for estimating sparse graphical models which fits a sparse linear regression locally at each node of the graph via the Lasso estimator. Using a recently suggested online, temporally adaptive implementation of the Lasso, we propose an algorithm for streaming graphical model selection over sensor networks. With battery consumption minimization applications in mind, we use this algorithm as the basis of an adaptive querying scheme. We discuss implementation issues in the context of environmental monitoring using sensor networks, where the objective is short-term forecasting of local wind direction. The algorithm is tested against real UK weather data and conclusions are drawn about certain tradeoffs inherent in decentralized sensor networks data analysis. © 2010 The Author. Published by Oxford University Press on behalf of The British Computer Society. All rights reserved.

软件成本估算方法及应用

软件成本估算从20世纪60年代发展至今,在软件开发过程中一直扮演着重要角色.按照基于算法模型的方法、非基于算法模型的方法以及组合方法的分类方式,全面回顾、分析了软件成本估算的各种代表性方法,也归纳讨论了与成本估算强相关的软件规模度量问题.在此基础上,进一步研究了软件成本估算方法的评价标准,并给出了一个应用实例及其分析.最后,从估算模型、估算演进、估算应用、估算内容、工具支持和人为因素6个方面,指出了软件成本估算方法下一步的主要发展趋势.

基于度量工具的软件成本估算模型使用方法

输入的主观性以及输入过多是妨碍软件成本估算模型实际应用效果的重要影响因素.针对以上问题,提出了一种基于度量工具的软件成本估算模型使用方法.该方法通过引入统计理论中的工具变量,将度量工具所采集的度量元数据自动转换为软件成本估算模型的输入.这一方面可以避免模型校准和估算过程中输入的主观性与不一致性,提高了估算结果的准确性与可靠性;另一方面能减少估算人员的手工操作,提高工作效率,增加了软件成本估算模型的可用性.结合具体实例说明了所提出方法的可行性与有效性.

产品线成本模型的比较与分析

为给软件产品线决策者应用软件产品线模型提供理论上的参考,综合分析比较了近年来的20种软件产品线模型,在对软件产品线模型的投资循环、重用方式、货币时间价值、经济函数、成本因子和重用成本等方面因素进行细致分析的基础上提出了软件产品线模型的比较框架,在该框架内着重分析了其中5种典型的软件产品线模型,对应用软件产品线开发方式的成本估算和投资分析做了细致分析,并对当前软件产品线模型时存在的问题和发展方向进行了探讨.