854 resultados para large scale linear system
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The article introduces a novel platform for conducting controlled and risk-free driving and traveling behavior studies, called Cyber-Physical System Simulator (CPSS). The key features of CPSS are: (1) simulation of multiuser immersive driving in a threedimensional (3D) virtual environment; (2) integration of traffic and communication simulators with human driving based on dedicated middleware; and (3) accessibility of multiuser driving simulator on popular software and hardware platforms. This combination of features allows us to easily collect large-scale data on interesting phenomena regarding the interaction between multiple user drivers, which is not possible with current single-user driving simulators. The core original contribution of this article is threefold: (1) we introduce a multiuser driving simulator based on DiVE, our original massively multiuser networked 3D virtual environment; (2) we introduce OpenV2X, a middleware for simulating vehicle-to-vehicle and vehicle to infrastructure communication; and (3) we present two experiments based on our CPSS platform. The first experiment investigates the “rubbernecking” phenomenon, where a platoon of four user drivers experiences an accident in the oncoming direction of traffic. Second, we report on a pilot study about the effectiveness of a Cooperative Intelligent Transport Systems advisory system.
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In elite sports, nearly all performances are captured on video. Despite the massive amounts of video that has been captured in this domain over the last 10-15 years, most of it remains in an 'unstructured' or 'raw' form, meaning it can only be viewed or manually annotated/tagged with higher-level event labels which is time consuming and subjective. As such, depending on the detail or depth of annotation, the value of the collected repositories of archived data is minimal as it does not lend itself to large-scale analysis and retrieval. One such example is swimming, where each race of a swimmer is captured on a camcorder and in-addition to the split-times (i.e., the time it takes for each lap), stroke rate and stroke-lengths are manually annotated. In this paper, we propose a vision-based system which effectively 'digitizes' a large collection of archived swimming races by estimating the location of the swimmer in each frame, as well as detecting the stroke rate. As the videos are captured from moving hand-held cameras which are located at different positions and angles, we show our hierarchical-based approach to tracking the swimmer and their different parts is robust to these issues and allows us to accurately estimate the swimmer location and stroke rates.
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Differential response has long been utilized by statutory child protection systems in Australia. This article describes the advent and history of Victoria's differential response system, with a particular focus on the Child FIRST and IFS programme. This program entails a partnership arrangement between the Department of Human Services child protection services and community-based, not-for-profit agencies to provide a diverse range of early intervention and prevention services. The findings of a recent external service system evaluation, a judicial inquiry, and the large-scale Child and Family Services Outcomes Survey of parents/carers perspectives of their service experiences are used to critically examine the effectiveness of this differential response approach. Service-user perspectives of the health and wellbeing of children and families are identified, as well as the recognized implementation issues posing significant challenges for the goal of an integrated partnership system. The need for ongoing reform agendas is highlighted along with the policy, program and structural tensions that exist in differential response systems, which are reliant upon partnerships and shared responsibilities for protecting children and assisting vulnerable families. Suggestions are made for utilizing robust research and evaluation that gives voice to service users and promotes their rights and interests.
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Linear assets are engineering infrastructure, such as pipelines, railway lines, and electricity cables, which span long distances and can be divided into different segments. Optimal management of such assets is critical for asset owners as they normally involve significant capital investment. Currently, Time Based Preventive Maintenance (TBPM) strategies are commonly used in industry to improve the reliability of such assets, as they are easy to implement compared with reliability or risk-based preventive maintenance strategies. Linear assets are normally of large scale and thus their preventive maintenance is costly. Their owners and maintainers are always seeking to optimize their TBPM outcomes in terms of minimizing total expected costs over a long term involving multiple maintenance cycles. These costs include repair costs, preventive maintenance costs, and production losses. A TBPM strategy defines when Preventive Maintenance (PM) starts, how frequently the PM is conducted and which segments of a linear asset are operated on in each PM action. A number of factors such as required minimal mission time, customer satisfaction, human resources, and acceptable risk levels need to be considered when planning such a strategy. However, in current practice, TBPM decisions are often made based on decision makers’ expertise or industrial historical practice, and lack a systematic analysis of the effects of these factors. To address this issue, here we investigate the characteristics of TBPM of linear assets, and develop an effective multiple criteria decision making approach for determining an optimal TBPM strategy. We develop a recursive optimization equation which makes it possible to evaluate the effect of different maintenance options for linear assets, such as the best partitioning of the asset into segments and the maintenance cost per segment.
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Blasting is an integral part of large-scale open cut mining that often occurs in close proximity to population centers and often results in the emission of particulate material and gases potentially hazardous to health. Current air quality monitoring methods rely on limited numbers of fixed sampling locations to validate a complex fluid environment and collect sufficient data to confirm model effectiveness. This paper describes the development of a methodology to address the need of a more precise approach that is capable of characterizing blasting plumes in near-real time. The integration of the system required the modification and integration of an opto-electrical dust sensor, SHARP GP2Y10, into a small fixed-wing and multi-rotor copter, resulting in the collection of data streamed during flight. The paper also describes the calibration of the optical sensor with an industry grade dust-monitoring device, Dusttrak 8520, demonstrating a high correlation between them, with correlation coefficients (R2) greater than 0.9. The laboratory and field tests demonstrate the feasibility of coupling the sensor with the UAVs. However, further work must be done in the areas of sensor selection and calibration as well as flight planning.
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Any kind of imbalance in the operation of a wind turbine has adverse effect on the downstream torsional components as well as tower structure. It is crucial to detect imbalance at its very inception. The identification of the type of imbalance is also required so that appropriate measures of fault accommodation can be performed in the control system. In particular, it is important to distinguish between mass and aerodynamic imbalance. While the former is gradually caused by a structural anomaly (e.g. ice deposition, moisture accumulation inside blade), the latter is generally associated to a fault in the pitch control system. This paper proposes a technique for the detection and identification of imbalance fault in large scale wind turbines. Unlike most other existing method it requires only the rotor speed signal which is readily available in existing turbines. Signature frequencies have been proposed in this work to identify imbalance type based on their physical phenomenology. The performance of this technique has been evaluated by simulations using an existing benchmark model. The effectiveness of the proposed method has been confirmed by the simulation results.
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Network topology and routing are two important factors in determining the communication costs of big data applications at large scale. As for a given Cluster, Cloud, or Grid system, the network topology is fixed and static or dynamic routing protocols are preinstalled to direct the network traffic. Users cannot change them once the system is deployed. Hence, it is hard for application developers to identify the optimal network topology and routing algorithm for their applications with distinct communication patterns. In this study, we design a CCG virtual system (CCGVS), which first uses container-based virtualization to allow users to create a farm of lightweight virtual machines on a single host. Then, it uses software-defined networking (SDN) technique to control the network traffic among these virtual machines. Users can change the network topology and control the network traffic programmingly, thereby enabling application developers to evaluate their applications on the same system with different network topologies and routing algorithms. The preliminary experimental results through both synthetic big data programs and NPB benchmarks have shown that CCGVS can represent application performance variations caused by network topology and routing algorithm.
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The problem of identifying parameters of time invariant linear dynamical systems with fractional derivative damping models, based on a spatially incomplete set of measured frequency response functions and experimentally determined eigensolutions, is considered. Methods based on inverse sensitivity analysis of damped eigensolutions and frequency response functions are developed. It is shown that the eigensensitivity method requires the development of derivatives of solutions of an asymmetric generalized eigenvalue problem. Both the first and second order inverse sensitivity analyses are considered. The study demonstrates the successful performance of the identification algorithms developed based on synthetic data on one, two and a 33 degrees of freedom vibrating systems with fractional dampers. Limited studies have also been conducted by combining finite element modeling with experimental data on accelerances measured in laboratory conditions on a system consisting of two steel beams rigidly joined together by a rubber hose. The method based on sensitivity of frequency response functions is shown to be more efficient than the eigensensitivity based method in identifying system parameters, especially for large scale systems.
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This joint DPI/Burdekin Shire Council project assessed the efficacy of a pilot-scale biological remediation system to recover Nitrogen (N) and Phosphorous (P) nutrients from secondary treated municipal wastewater at the Ayr Sewage Treatment Plant. Additionally, this study considered potential commercial uses for by-products from the treatment system. Knowledge gained from this study can provide directions for implementing a larger-scale final effluent treatment protocol on site at the Ayr plant. Trials were conducted over 10 months and assessed nutrient removal from duckweed-based treatments and an algae/fish treatment – both as sequential and as stand-alone treatment systems. A 42.3% reduction in Total N was found through the sequential treatment system (duckweed followed by algae/fish treatment) after 6.6 days Effluent Retention Time (E.R.T.). However, duckweed treatment was responsible for the majority of this nutrient recovery (7.8 times more effective than algae/fish treatment). Likewise, Total P reduction (15.75% reduction after 6.6 days E.R.T.) was twice as great in the duckweed treatment. A phytoplankton bloom, which developed in the algae/fish tanks, reduced nutrient recovery in this treatment. A second trial tested whether the addition of fish enhanced duckweed treatment by evaluating systems with and without fish. After four weeks operation, low DO under the duckweed blanket caused fish mortalities. Decomposition of these fish led to an additional organic load and this was reflected in a breakdown of nitrogen species that showed an increase in organic nitrogen. However, the Dissolved Inorganic Nitrogen (DIN: ammonia, nitrite and nitrate) removal was similar between treatments with and without fish (57% and 59% DIN removal from incoming, respectively). Overall, three effluent residence times were evaluated using duckweed-based treatments; i.e. 3.5 days, 5.5 days and 10.4 days. Total N removal was 37.5%, 55.7% and 70.3%, respectively. The 10.4-day E.R.T. trial, however, was evaluated by sequential nutrient removal through the duckweed-minus-fish treatment followed by the duckweed-plus-fish treatment. Therefore, the 70.3% Total N removal was lower than could have been achieved at this retention time due to the abovementioned fish mortalities. Phosphorous removal from duckweed treatments was greatest after 10.4-days E.R.T. (13.6%). Plant uptake was considered the most important mechanism for this P removal since there was no clay substrate in the plastic tanks that could have contributed to P absorption as part of the natural phosphorous cycle. Duckweed inhibited phytoplankton production (therefore reducing T.S.S) and maintained pH close to neutral. DO beneath the duckweed blanket fell to below 1ppm; however, this did not limit plant production. If fish are to be used as part of the duckweed treatment, air-uplifts can be installed that maintain DO levels without disturbing surface waters. Duckweed grown in the treatments doubled its biomass on average every 5.7 days. On a per-surface area basis, 1.23kg/m2 was harvested weekly. Moisture content of duckweed was 92%, equating to a total dry weight harvest of 0.098kg/m2/week. Nutrient analysis of dried duckweed gave an N content of 6.67% and a P content of 1.27%. According to semi-quantitative analyses, harvested duckweed contained no residual elements from the effluent stream that were greater than ANZECC toxicant guidelines proposed for aquaculture. In addition, jade perch, a local aquaculture species, actively consumed and gained weight on harvested duckweed, suggesting potential for large-scale fish production using by-products from the effluent treatment process. This suggests that a duckweed-based system may be one viable option for tertiary treatment of Ayr municipal wastewater. The tertiary detention lagoon proposed by the Burdekin Shire Council, consisting of six bays approximately 290 x 35 metres (x 1.5 metres deep), would be suitable for duckweed culture with minor modification to facilitate the efficient distribution of duckweed plants across the entire available growing surface (such as floating containment grids). The effluent residence time resulting from this proposed configuration (~30 days) should be adequate to recover most effluent nutrients (certainly N) based on the current trial. Duckweed harvest techniques on this scale, however, need to be further investigated. Based on duckweed production in the current trial (1.23kg/m2/week), a weekly harvest of approximately 75 000kg (wet weight) could be expected from the proposed lagoon configuration under full duckweed production. A benefit of the proposed multi-bay lagoon is that full lagoon production of duckweed may not be needed to restore effluent to a desirable standard under the present nutrient load, and duckweed treatment may be restricted to certain bays. Restored effluent could be released without risk of contaminating the receiving waterway with duckweed by evacuating water through an internal standpipe located mid-way in the water column.
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Sichuanissa Tiibetin ylängön metsäkato on pysähtynyt mutta eroosio-ongelmat jatkuvat Viikin tropiikki-instituutin tutkija Ping ZHOU kartoitti trooppisen metsänhoidon alaan kuuluvassa väitöskirjatyössään maaperän eroosioalttiutta ja sen riippuvuutta metsäkasvillisuudesta Jangtsen tärkeää sivuhaaraa Min-jokea ympäröivällä n. 7400 neliökilometrin suuruisella valuma-alueella Sichuanin Aba-piirikunnassa. Aineistonaan hän käytti muun muassa satelliittikartoitustietoja ja mittaustuloksia yli 600 maastokoealalta. Tutkimuksen nimi suomeksi on "Maaperän eroosion mallinnus ja vuoristoisen valuma-alueen ekologinen ennallistaminen Sichuanissa Kiinassa". Aikaisempien tutkimusten perusteella oli tiedossa että metsien häviäminen tällä alueella pysähtyi jo 1980-luvun alussa. Sen jälkeen on metsien pinta-ala hitaasti kasvanut etupäässä sen vuoksi, että teollinen puunhakkuu luonnonmetsissä kiellettiin kokonaan v. 1998 ja 25 astetta jyrkemmillä rinteillä myös maatalouden harjoittaminen on saatu lopetetuksi viljelijöille tarjottujen taloudellisten houkuttimien avulla. Täten myös pelto- ja laidunmaata on voitu ennallistaa metsäksi. Ping Zhou pystyi jakamaan 5700 metrin korkeuteen saakka kohoavan vuoristoalueen eroosioalttiudeltaan erilaisiin vyöhykkeisiin rinteen kaltevuuden, sademäärän, kasvipeitteen ja maalajin perusteella. Noin 15 prosentilla tutkitun valuma-alueen pinta-alasta, lähinnä Min-joen pääuomaa ympäröivillä jyrkillä rinteillä, eroosioriski oli suuri tai erittäin suuri. Eri tyyppisellä kasvillisuudella oli hyvin erilainen vaikutus eroosioalttiuteen, ja myös alueen sijainti vuoriston eri korkeuksilla vaikutti eroosioon. Säästyneet lähes luonnontilaiset havumetsät, joita on etupäässä vuoriston ylimmissä osissa 2600-4000 metrin korkeudella, edistävät tehokkaasti metsän luontaista uudistumista ja levittäytymistä vaurioituneille alueille. Säilyneiden metsien puulajikoostumus antoi tutkimuksessa mahdollisuuden ennustaa metsien tulevaa kehitystä koko tutkitulla valuma-alueella sen eri korkeusvyöhykkeissä ja eri maaperätyypeillä. Ennallistamisen kannalta ongelmallisimpia olivat alueet joilta metsäpeite oli lähinnä puiden teollisen hakkuun vuoksi kokonaan hävinnyt ja joilla maaperä yleisesti oli eroosion pahoin kuluttama. Näillä alueilla ei ole tehty juuri mitään uudistamis- tai ennallistamistoimenpiteitä. Niillä metsien ennallistaminen vaatii myös puiden tai pensaiden istuttamista. Tähän sopivia ovat erityisesti ilmakehän typpeä sitovat lajit, joista alueella kasvaa luontaisena mm. sama tyrnilaji joka esiintyy myös Suomessa. Työssä tutkittiin yli kahdeksankymmenen paikallisen luontaisen puulajin (joista peräti noin kolmannes on havupuulajeja) ekologisia ominaisuuksia ja soveltuvuutta metsien ennallistamiseen. Avainasemassa työn onnistumisen kannalta ovat nyt paikalliset asukkaat, joiden maankäytön muutokset ovat jo selvästi edistänet luonnonmetsän ennalleen palautumista. Suomen Akatemia rahoitti vuosina 2004-2006 VITRI:n tutkimushanketta, josta Ping Zhou'n väitöskirjatyö muodosti keskeisen osan. Kenttätyö Sichuanissa avasi mahdollisuuden hedelmälliseen monitieteiseen yhteistyöhön ja tutkijavaihtoon Kiinan tiedeakatemian alaisen Chengdun biologiainstituutin (CIB) kanssa; tämä tieteellinen kanssakäyminen jatkuu edelleen.
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The purpose of this study was to extend understanding of how large firms pursuing sustained and profitable growth manage organisational renewal. A multiple-case study was conducted in 27 North American and European wood-industry companies, of which 11 were chosen for closer study. The study combined the organisational-capabilities approach to strategic management with corporate-entrepreneurship thinking. It charted the further development of an identification and classification system for capabilities comprising three dimensions: (i) the dynamism between firm-specific and industry-significant capabilities, (ii) hierarchies of capabilities and capability portfolios, and (iii) their internal structure. Capability building was analysed in the context of the organisational design, the technological systems and the type of resource-bundling process (creating new vs. entrenching existing capabilities). The thesis describes the current capability portfolios and the organisational changes in the case companies. It also clarifies the mechanisms through which companies can influence the balance between knowledge search and the efficiency of knowledge transfer and integration in their daily business activities, and consequently the diversity of their capability portfolio and the breadth and novelty of their product/service range. The largest wood-industry companies of today must develop a seemingly dual strategic focus: they have to combine leading-edge, innovative solutions with cost-efficient, large-scale production. The use of modern technology in production was no longer a primary source of competitiveness in the case companies, but rather belonged to the portfolio of basic capabilities. Knowledge and information management had become an industry imperative, on a par with cost effectiveness. Yet, during the period of this research, the case companies were better in supporting growth in volume of the existing activity than growth through new economic activities. Customer-driven, incremental innovation was preferred over firm-driven innovation through experimentation. The three main constraints on organisational renewal were the lack of slack resources, the aim for lean, centralised designs, and the inward-bound communication climate.
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The simultaneous state and parameter estimation problem for a linear discrete-time system with unknown noise statistics is treated as a large-scale optimization problem. The a posterioriprobability density function is maximized directly with respect to the states and parameters subject to the constraint of the system dynamics. The resulting optimization problem is too large for any of the standard non-linear programming techniques and hence an hierarchical optimization approach is proposed. It turns out that the states can be computed at the first levelfor given noise and system parameters. These, in turn, are to be modified at the second level.The states are to be computed from a large system of linear equations and two solution methods are considered for solving these equations, limiting the horizon to a suitable length. The resulting algorithm is a filter-smoother, suitable for off-line as well as on-line state estimation for given noise and system parameters. The second level problem is split up into two, one for modifying the noise statistics and the other for modifying the system parameters. An adaptive relaxation technique is proposed for modifying the noise statistics and a modified Gauss-Newton technique is used to adjust the system parameters.
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Anaerobic digestion is a viable on-site treatment technology for rich organic waste streams such as food waste and blackwater. In contrast to large-scale municipal wastewater treatment plants which are typically located away from the community, the effluent from any type of on-site system is a potential pathogenic hazard because of the intimacy of the system to the community. The native concentrations of the pathogen indicators Escherichia coli, Clostridium perfringens and somatic coliphage were tracked for 30 days under stable operation (organic loading rate (OLR) = 1.8 kgCOD m(-3) day(-1), methane yield = 52% on a chemical oxygen demand (COD) basis) of a two-stage laboratory-scale digester treating a mixture of food waste and blackwater. E. coli numbers were reduced by a factor of 10(6.4) in the thermophilic stage, from 10(7.5+/-0.3) to 10(1.1+/-0.1) cfu 100 mL(-1), but regenerated by a factor of 10(4) in the mesophilic stage. Neither the thermophilic nor mesophilic stages had any significant impact on C. perfringens concentrations. Coliphage concentrations were reduced by a factor of 10(1.4) across the two stages. The study shows that anaerobic digestion only reduces pathogen counts marginally but that counts in effluent samples could be readily reduced to below detection limits by filtration through a 0.22 microm membrane, to investigate membrane filtration as a possible sanitation technique.
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One of the critical issues in large scale commercial exploitation of MEMS technology is its system integration. In MEMS, a system design approach requires integration of varied and disparate subsystems with one of a kind interface. The physical scales as well as the magnitude of signals of various subsystems vary widely. Known and proven integration techniques often lead to considerable loss in advantages the tiny MEMS sensors have to offer. Therefore, it becomes imperative to think of the entire system at the outset, at least in terms of the concept design. Such design entails various aspects of the system ranging from selection of material, transduction mechanism, structural configuration, interface electronics, and packaging. One way of handling this problem is the system-in-package approach that uses optimized technology for each function using the concurrent hybrid engineering approach. The main strength of this design approach is the fast time to prototype development. In the present work, we pursue this approach for a MEMS load cell to complete the process of system integration for high capacity load sensing. The system includes; a micromachined sensing gauge, interface electronics and a packaging module representing a system-in-package ready for end characterization. The various subsystems are presented in a modular stacked form using hybrid technologies. The micromachined sensing subsystem works on principles of piezo-resistive sensing and is fabricated using CMOS compatible processes. The structural configuration of the sensing layer is designed to reduce the offset, temperature drift, and residual stress effects of the piezo-resistive sensor. ANSYS simulations are carried out to study the effect of substrate coupling on sensor structure and its sensitivity. The load cell system has built-in electronics for signal conditioning, processing, and communication, taking into consideration the issues associated with resolution of minimum detectable signal. The packaged system represents a compact and low cost solution for high capacity load sensing in the category of compressive type load sensor.