Consumer spatial shopping behaviour analysis: A case study of the Kitchener CMA (Ontario)

Many marketing geographers concern themselves with the study of consumer spatial choice behaviour. Addressing some of the concerns, this thesis provides an evidence of customers’ spatial shopping behaviour at the study region of Kitchener Census Metropolitan Area (CMA). A customer’s spatial choice decision-making in the study area was first assumed to be a two-levelled process: regional and subregional level. This study was to identify the factors motivating consumers’ choice on where to shop at these two levels. A previous 804 households’ shopping behaviour survey conducted by Dr. A. Hecht in 1986 was used as the data basis of this study. A behavioral model named Multinomial Logit Model was utilized as a major research method to investigate the factors influencing shoppers spatial choice decision-making process in light of selected attributes of thirteen shopping centres and the characteristics of consumers themselves. A choice frequency analysis was also employed to identify the influencing factors at the different levels. The results indicate that the distance from a shopper’s residence to the shopping centre decreases the probabilities of an individual patronizing that centre at the regional level, while the size of the shopping centre is mostly important for consumers at the subregional level

A Self-Adaptive Chaos Particle Swarm Optimization Algorithm

As a new evolutionary algorithm, particle swarm optimization (PSO) achieves integrated evolution through the information between the individuals. All the particles have the ability to adjust their own speed and remember the optimal positions they have experienced. This algorithm has solved many practical engineering problems and achieved better optimization effect. However, PSO can easily get trapped in local extremum, making it fail to get the global optimal solution and reducing its convergence speed. To settle these deficiencies, this paper has proposed an adaptive chaos particle swarm optimization (ACPSO) based on the idea of chaos optimization after analyzing the basic principles of PSO. This algorithm can improve the population diversity and the ergodicity of particle search through the property of chaos; adjust the inertia weight according to the premature convergence of the population and the individual fitness; consider the global optimization and local optimization; effectively avoid premature convergence and improve algorithm efficiency. The experimental simulation has verified its effectiveness and superiority

A Simple and High Performing Rate Control Initialization Method for H.264 AVC Coding Based on Motion Vector Map and Spatial Complexity at Low Bitrate

The temporal complexity of video sequences can be characterized by motion vector map which consists of motion vectors of each macroblock (MB). In order to obtain the optimal initial QP (quantization parameter) for the various video sequences which have different spatial and temporal complexities, this paper proposes a simple and high performance initial QP determining method based on motion vector map and temporal complexity to decide an initial QP in given target bit rate. The proposed algorithm produces the reconstructed video sequences with outstanding and stable quality. For any video sequences, the initial QP can be easily determined from matrices by target bit rate and mapped spatial complexity using proposed mapping method. Experimental results show that the proposed algorithm can show more outstanding objective and subjective performance than other conventional determining methods

Production forecast of China׳s rare earths based on the Generalized Weng model and policy recommendations

AbstractChina is currently the largest producer of rare earths in the world, mining at least 90% of world total production. Because of China׳s dominant position in global rare earths production and the constant development of rare earths terminal industries, the study of China׳s rare earth supply trends has gradually been a hot topic of world interest. However, the literature shows that previous research has mainly focused on the estimation of rare earth supply and its influence based on experiential judge of current and premonitory new rare earth production capacity, rather than on quantitative modeling. The results are usually estimations of the productions of near future rather than longer term. Forecasts by mine types are particularly rare. Considering the different applications and demands of different rare earth elements, the Generalized Weng model, a widely used quantitative model in exhaustible resource forecast, is adopted in this study to predict the production of the three major rare earths in China (namely, mixed rare earth, bastnasite and ion-absorbed rare earth) before 2050. The results show that production of mixed rare earth will peak in 2014 at 62,757t, followed thereafter by an annual decline of 2%; production of bastnasite will peak in 2018 at 32,312t, preceded by an annual increase of 1.67% and followed by an annual decrease of 4%; production of ion-absorbed rare earth will peak in 2024 at 45,793t, preceded by an annual increase of 1.72% and followed by an annual decrease of 4%. Based on these findings, Chinese government should enforce environmental and resource exhaustible taxes soon and different domestic regulations for different rare earths according to their different production potential. Countries without resource endowments should make efforts to develop rare earth recycling technologies and seek substitutes for rare earth resources, in addition to keeping good international trading relationships. Countries with some kind of rare earths should start or restart their rare earth mines to gradually reduce dependence on China׳s supply

Retinal vessel segmentation:An efficient graph cut approach with Retinex and local phase

Our application concerns the automated detection of vessels in retinal images to improve understanding of the disease mechanism, diagnosis and treatment of retinal and a number of systemic diseases. We propose a new framework for segmenting retinal vasculatures with much improved accuracy and efficiency. The proposed framework consists of three technical components: Retinex-based image inhomogeneity correction, local phase-based vessel enhancement and graph cut-based active contour segmentation. These procedures are applied in the following order. Underpinned by the Retinex theory, the inhomogeneity correction step aims to address challenges presented by the image intensity inhomogeneities, and the relatively low contrast of thin vessels compared to the background. The local phase enhancement technique is employed to enhance vessels for its superiority in preserving the vessel edges. The graph cut-based active contour method is used for its efficiency and effectiveness in segmenting the vessels from the enhanced images using the local phase filter. We have demonstrated its performance by applying it to four public retinal image datasets (3 datasets of color fundus photography and 1 of fluorescein angiography). Statistical analysis demonstrates that each component of the framework can provide the level of performance expected. The proposed framework is compared with widely used unsupervised and supervised methods, showing that the overall framework outperforms its competitors. For example, the achieved sensitivity (0:744), specificity (0:978) and accuracy (0:953) for the DRIVE dataset are very close to those of the manual annotations obtained by the second observer

Cooperative low-rank models for removing stripe noise from OCTA images

Optical coherence tomography angiography (OCTA) is an emerging non-invasive imaging technique for imaging the microvasculature of the eye based on phase variance or amplitude decorrelation derived from repeated OCT images of the same tissue area. Stripe noise occurs during the OCTA acquisition process due to the involuntary movement of the eye. To remove the stripe noise (or ‘destriping’) effectively, we propose two novel image decomposition models to simultaneously destripe all the OCTA images of the same eye cooperatively: cooperative uniformity destriping (CUD) model and cooperative similarity destriping (CSD) model. Both the models consider stripe noise by low-rank constraint but in different ways: the CUD model assumes that stripe noise is identical across all the layers while the CSD model assumes that the stripe noise at different layers are different and have to be considered in the model. Compared to the CUD model, CSD is a more general solution for real OCTA images. An efficient solution (CSD+) is developed for model CSD to reduce the computational complexity. The models were extensively evaluated against state-of-the-art methods on both synthesized and real OCTA datasets. The experiments demonstrated not only the effectiveness of the CSD and CSD+ models in terms of peak signal-to-noise ratio (PSNR) and structural similarity index (SSIM) and CSD+ is twice faster than CSD, but also their beneficiary effect on the vessel segmentation of OCTA images. We expect our models will become a powerful tool for clinical applications

Resource Distribution, Interprovincial Trade, and Embodied Energy: A Case Study of China

Based on data from 2007 input-output tables for each province, we estimated the energy embodied in China's interprovincial trade through input-output analysis. The results show that a sizable transfer of energy is embodied in China's interprovincial trade, and the transfer goes from the central and western provinces, which have higher energy endowments, to the eastern and coastal provinces, which have more developed economies. The provinces with the greatest net inflow of embodied energy via interprovincial trade were Zhejiang, Guangdong, Beijing, Shandong, and Jiangsu. The provinces with the greatest net outflow of embodied energy were Inner Mongolia, Shanxi, Shaanxi, Xinjiang, and Heilongjiang. To effectively reduce China's energy consumption, it is vital to adhere not only to the producer responsibility principle but also to the consumer responsibility principle. In particular, the economically developed provinces with substantial net inflows of embodied energy in interprovincial trade should provide support to the provinces from which the embodied energy outflows come

Resource Distribution, Interprovincial Trade, and Embodied Energy: A Case Study of China

Based on data from 2007 input-output tables for each province, we estimated the energy embodied in China’s interprovincial trade through input-output analysis. The results show that a sizable transfer of energy is embodied in China’s interprovincial trade, and the transfer goes from the central and western provinces, which have higher energy endowments, to the eastern and coastal provinces, which have more developed economies. The provinces with the greatest net inflow of embodied energy via interprovincial trade were Zhejiang, Guangdong, Beijing, Shandong, and Jiangsu. The provinces with the greatest net outflow of embodied energy were Inner Mongolia, Shanxi, Shaanxi, Xinjiang, and Heilongjiang. To effectively reduce China’s energy consumption, it is vital to adhere not only to the producer responsibility principle but also to the consumer responsibility principle. In particular, the economically developed provinces with substantial net inflows of embodied energy in interprovincial trade should provide support to the provinces from which the embodied energy outflows come