925 resultados para Tipo de interés real


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The purpose of this scoping paper is to offer an overview of the literature to determine the development to date in the area of residential real estate agency academic and career education in respect to Foreign Direct Investment (FDI) transactions and implications in Australia. This paper will review studies on the issue of foreign real estate ownership and FDI in Australian real estate markets to develop an understanding of the current state of knowledge on residential real estate agency practice, career education and real estate licensing requirements in Australia. The distinction between the real estate profession education, compared to other professions such as accounting, legal and finance is based on the intensity of the professional career training prior or post formal academic training. Real estate education could be carried out with relatively higher standards in terms of licensing requirement, career and academic education. As FDI in the Australian real estate market is a complex globalisation and economic phenomenon, a simple content of residential real estate training and education may not promote proper management or capacity in dealing with relevant foreign residential property market transaction. The preliminary summarising from the literature of residential real estate agency education, with its current relevant or emerging licensing requirement are focused on its role and effectiveness and impact in residential real estate market. Particular focus will be directed to the FDI relevant residential real estate agency transactions and practices, which have been strongly influenced by the current residential real estate market and agency practices. Taken together, there are many opportunities for future research to extend our understanding and improving the residential real estate agency education and training of Foreign Direct Investment in the Australian residential real estate sector.

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Real Estate Agency education in Australia has undergone many changes during the last 40 years. This is primarily due to the changing nature of consumer protection provided by government and the expectation of increased fields of knowledge relating to real estate transactions. Each state and territory within Australia has a range of regulatory bodies to oversee consumer protection and the distinct licenses and educational requirements that comprise their regimes. Since the 1970’s minimum educational requirements in New South Wales are prescribed for real estate agency work. However, very little research exists in the Australian literature, where an analysis has been undertaken to evaluate these changes, which includes course content, hours allocated for each subject, assessment criteria for each subject,the educational qualification attained, and the requirement for industry experience as a pre-requisite for licensing approval. It is argued that the change to educational requirements, has impacted negatively for the consumer, with an increase in consumer complaints, particularly during the last 10 years.

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This paper proposes to adopt data envelopment analysis (DEA) based Malmquist total factor productivity (TFP) indices methods to evaluate the effect of mergers and acquisitions (M&As) on acquirers in short-term and long-term window. Based on analyzing 32 M&A deals conducted by Chinese real estate firms from 2000-2011, the study result demonstrate that the effect of M&A on developers’ performance is positive. Through M&A, the developers’ Malmquist TFP experienced a steady growth; their technology has got noticeable progress immediately after acquisition; and their technical efficiency has suffered a slight decrease in short-term after acquisition, but then achieved marked increase in the long-term when realization of integration and synergy. However, there is no evidence that the real estate firms have achieved scale efficiency improvement after M&A in either short-term or long-term.

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Price based technique is one way to handle increase in peak demand and deal with voltage violations in residential distribution systems. This paper proposes an improved real time pricing scheme for residential customers with demand response option. Smart meters and in-home display units are used to broadcast the price and appropriate load adjustment signals. Customers are given an opportunity to respond to the signals and adjust the loads. This scheme helps distribution companies to deal with overloading problems and voltage issues in a more efficient way. Also, variations in wholesale electricity prices are passed on to electricity customers to take collective measure to reduce network peak demand. It is ensured that both customers and utility are benefitted by this scheme.

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This paper describes the theory and practice for a stable haptic teleoperation of a flying vehicle. It extends passivity-based control framework for haptic teleoperation of aerial vehicles in the longest intercontinental setting that presents great challenges. The practicality of the control architecture has been shown in maneuvering and obstacle-avoidance tasks over the internet with the presence of significant time-varying delays and packet losses. Experimental results are presented for teleoperation of a slave quadrotor in Australia from a master station in the Netherlands. The results show that the remote operator is able to safely maneuver the flying vehicle through a structure using haptic feedback of the state of the slave and the perceived obstacles.

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The ability to measure surface temperature and represent it on a metrically accurate 3D model has proven applications in many areas such as medical imaging, building energy auditing, and search and rescue. A system is proposed that enables this task to be performed with a handheld sensor, and for the first time with results able to be visualized and analyzed in real-time. A device comprising a thermal-infrared camera and range sensor is calibrated geometrically and used for data capture. The device is localized using a combination of ICP and video-based pose estimation from the thermal-infrared video footage which is shown to reduce the occurrence of failure modes. Furthermore, the problem of misregistration which can introduce severe distortions in assigned surface temperatures is avoided through the use of a risk-averse neighborhood weighting mechanism. Results demonstrate that the system is more stable and accurate than previous approaches, and can be used to accurately model complex objects and environments for practical tasks.

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Technological advances have led to an influx of affordable hardware that supports sensing, computation and communication. This hardware is increasingly deployed in public and private spaces, tracking and aggregating a wealth of real-time environmental data. Although these technologies are the focus of several research areas, there is a lack of research dealing with the problem of making these capabilities accessible to everyday users. This thesis represents a first step towards developing systems that will allow users to leverage the available infrastructure and create custom tailored solutions. It explores how this notion can be utilized in the context of energy monitoring to improve conventional approaches. The project adopted a user-centered design process to inform the development of a flexible system for real-time data stream composition and visualization. This system features an extensible architecture and defines a unified API for heterogeneous data streams. Rather than displaying the data in a predetermined fashion, it makes this information available as building blocks that can be combined and shared. It is based on the insight that individual users have diverse information needs and presentation preferences. Therefore, it allows users to compose rich information displays, incorporating personally relevant data from an extensive information ecosystem. The prototype was evaluated in an exploratory study to observe its natural use in a real-world setting, gathering empirical usage statistics and conducting semi-structured interviews. The results show that a high degree of customization does not warrant sustained usage. Other factors were identified, yielding recommendations for increasing the impact on energy consumption.

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Currently, the GNSS computing modes are of two classes: network-based data processing and user receiver-based processing. A GNSS reference receiver station essentially contributes raw measurement data in either the RINEX file format or as real-time data streams in the RTCM format. Very little computation is carried out by the reference station. The existing network-based processing modes, regardless of whether they are executed in real-time or post-processed modes, are centralised or sequential. This paper describes a distributed GNSS computing framework that incorporates three GNSS modes: reference station-based, user receiver-based and network-based data processing. Raw data streams from each GNSS reference receiver station are processed in a distributed manner, i.e., either at the station itself or at a hosting data server/processor, to generate station-based solutions, or reference receiver-specific parameters. These may include precise receiver clock, zenith tropospheric delay, differential code biases, ambiguity parameters, ionospheric delays, as well as line-of-sight information such as azimuth and elevation angles. Covariance information for estimated parameters may also be optionally provided. In such a mode the nearby precise point positioning (PPP) or real-time kinematic (RTK) users can directly use the corrections from all or some of the stations for real-time precise positioning via a data server. At the user receiver, PPP and RTK techniques are unified under the same observation models, and the distinction is how the user receiver software deals with corrections from the reference station solutions and the ambiguity estimation in the observation equations. Numerical tests demonstrate good convergence behaviour for differential code bias and ambiguity estimates derived individually with single reference stations. With station-based solutions from three reference stations within distances of 22–103 km the user receiver positioning results, with various schemes, show an accuracy improvement of the proposed station-augmented PPP and ambiguity-fixed PPP solutions with respect to the standard float PPP solutions without station augmentation and ambiguity resolutions. Overall, the proposed reference station-based GNSS computing mode can support PPP and RTK positioning services as a simpler alternative to the existing network-based RTK or regionally augmented PPP systems.

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Real-time image analysis and classification onboard robotic marine vehicles, such as AUVs, is a key step in the realisation of adaptive mission planning for large-scale habitat mapping in previously unexplored environments. This paper describes a novel technique to train, process, and classify images collected onboard an AUV used in relatively shallow waters with poor visibility and non-uniform lighting. The approach utilises Förstner feature detectors and Laws texture energy masks for image characterisation, and a bag of words approach for feature recognition. To improve classification performance we propose a usefulness gain to learn the importance of each histogram component for each class. Experimental results illustrate the performance of the system in characterisation of a variety of marine habitats and its ability to operate onboard an AUV's main processor suitable for real-time mission planning.

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Safety concerns in the operation of autonomous aerial systems require safe-landing protocols be followed during situations where the mission should be aborted due to mechanical or other failure. This article presents a pulse-coupled neural network (PCNN) to assist in the vegetation classification in a vision-based landing site detection system for an unmanned aircraft. We propose a heterogeneous computing architecture and an OpenCL implementation of a PCNN feature generator. Its performance is compared across OpenCL kernels designed for CPU, GPU, and FPGA platforms. This comparison examines the compute times required for network convergence under a variety of images to determine the plausibility for real-time feature detection.

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This paper presents the details of experimental studies on the effect of real support conditions on the shear strength of LiteSteel beams (LSB). The LSB has a unique shape of a channel beam with two rectangular hollow flanges, made using a unique manufacturing process. In some applications in the building industry LSBs are used with only one web side plate (WSP) at their supports and are not used with full height web side plates (WSP) at their supports. Past research studies showed that theses real support connections did not provide simply supported conditions. Many studies have been carried out to evaluate the behaviour and design of LSBs with simply supported conditions subject to pure bending and predominant shear actions. To date, however, no investigation has been conducted into the effect of real support conditions on the shear strength of LSBs. Hence detailed experimental studies were undertaken to investigate the shear behaviour and strength of LSBs with real support conditions. A total of 28 experimental tests were conducted as part of the studies. Simply supported test specimens of LSBs with aspect ratios of 1.0 and 1.5 were loaded at mid-span until failure. It was found that the effect of using one WSP on the shear behaviour of LSB is significant and there is about 25% shear capacity reduction due to the lateral movement of the bottom flange at the supports. Shear capacity of LSB was also found to decrease when full height WSPs were not used. Suitable support connections were developed to improve the shear capacity of LSBs based on test results.

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Orthotopic or intracardiac injection of human breast cancer cell lines into immunocompromised mice allows study of the molecular basis of breast cancer metastasis. We have established a quantitative real-time PCR approach to analyze metastatic spread of human breast cancer cells inoculated into nude mice via these routes. We employed MDA-MB-231 human breast cancer cells genetically tagged with a bacterial β-galactosidase (Lac-Z) retroviral vector, enabling their detection by TaqMan® real-time PCR. PCR detection was linear, specific, more sensitive than conventional PCR, and could be used to directly quantitate metastatic burden in bone and soft organs. Attesting to the sensitivity and specificity of the PCR detection strategy, as few as several hundred metastatic MDA-MB-231 cells were detectable in 100 μm segments of paraffin-embedded lung tissue, and only in samples adjacent to sections that scored positive by histological detection. Moreover, the measured real-time PCR metastatic burden in the bone environment (mouse hind-limbs, n = 48) displayed a high correlation to the degree of osteolytic damage observed by high resolution X-ray analysis (r2 = 0.972). Such a direct linear relationship to tumor burden and bone damage substantiates the so-called 'vicious cycle' hypothesis in which metastatic tumor cells promote the release of factors from the bone which continue to stimulate the tumor cells. The technique provides a useful tool for molecular and cellular analysis of human breast cancer metastasis to bone and soft organs, can easily be extended to other cell/marker/organ systems, and should also find application in preclinical assessment of anti-metastatic modalities.