Adversarial Convolutional Networks with Weak Domain-Transfer for Multi-sequence Cardiac MR Images Segmentation

Analysis and modeling of the ventricles and myocardium are important in the diagnostic and treatment of heart diseases. Manual delineation of those tissues in cardiac MR (CMR) scans is laborious and time-consuming. The ambiguity of the boundaries makes the segmentation task rather challenging. Furthermore, the annotations on some modalities such as Late Gadolinium Enhancement (LGE) MRI, are often not available. We propose an end-to-end segmentation framework based on convolutional neural network (CNN) and adversarial learning. A dilated residual U-shape network is used as a segmentor to generate the prediction mask; meanwhile, a CNN is utilized as a discriminator model to judge the segmentation quality. To leverage the available annotations across modalities per patient, a new loss function named weak domain-transfer loss is introduced to the pipeline. The proposed model is evaluated on the public dataset released by the challenge organizer in MICCAI 2019, which consists of 45 sets of multi-sequence CMR images. We demonstrate that the proposed adversarial pipeline outperforms baseline deep-learning methods.Comment: 9 pages, 4 figures, conferenc

A meshless sub-region radial point interpolation method for accurate calculation of crack tip fields

A new meshless sub-region radial point interpolation method (MS-RPIM) is proposed for linear elastic fracture mechanics. The Williams expansions of stress field for mode I/II crack is used as the trial functions in crack tip region, the meshless radial point interpolation is used for the rest of domain, and a mixed variational principle is used for discretisation. In contrast to existing meshless formulations, the present MS-RPIM requires only very few nodes around the crack tip to obtain smooth stress and accurate results and the SIFs can be directly obtained as part of the solution and no additional effort via post-processing

Optimization of cool roof and night ventilation in office buildings: A case study in Xiamen, China

Increasing roof albedo (using a “cool” roof) and night ventilation are passive cooling technologies that can reduce the cooling loads in buildings, but existing studies have not comprehensively explored the potential benefits of integrating these two technologies. This study combines an experiment in the summer and transition seasons with an annual simulation so as to evaluate the thermal performance, energy savings and thermal comfort improvement that could be obtained by coupling a cool roof with night ventilation. A holistic approach integrating sensitivity analysis and multi-objective optimization is developed to explore key design parameters (roof albedo, night ventilation air change rate, roof insulation level and internal thermal mass level) and optimal design options for the combined application of the cool roof and night ventilation. The proposed approach is validated and demonstrated through studies on a six-storey office building in Xiamen, a cooling-dominated city in southeast China. Simulations show that combining a cool roof with night ventilation can significantly decrease the annual cooling energy consumption by 27% compared to using a black roof without night ventilation and by 13% compared to using a cool roof without night ventilation. Roof albedo is the most influential parameter for both building energy performance and indoor thermal comfort. Optimal use of the cool roof and night ventilation can reduce the annual cooling energy use by 28% during occupied hours when air-conditioners are on and reduce the uncomfortable time slightly during occupied hours when air-conditioners are off

Effects of natural soiling and weathering on cool roof energy savings for dormitory buildings in Chinese cities with hot summers

Roofs with high-reflectance (solar reflectance) coating, commonly known as cool roofs, can stay cool in the sun, thereby reducing building energy consumption and mitigating the urban heat island. However, chemical-physical degradation and biological growth can decrease their solar reflectance and the ability to save energy. In this study, the solar spectral reflectance of 12 different roofing products with an initial albedo of 0.56–0.90 was measured before exposure and once every three months over 32 months. Specimens were exposed on the roofs of dormitory buildings in Xiamen and Chengdu, each major urban areas with hot summers. The albedos of high and medium-lightness coatings stabilized in the ranges 0.45–0.62 and 0.36–0.59 in both cities, respectively. This study yielded albedo loss exceeded those reported in the latest Chinese standard by 0.08–0.15. Finally, DesignBuilder (EnergyPlus) simulations estimate that a new cool roof with albedo 0.78 on a six-story dormitory building will yield annual site energy savings (heating and cooling) for the top floor, which are 8.01 kWh/m2 (24.2%) and 9.12 kWh/m2 (26.3%) per unit floor area in Xiamen and Chengdu, respectively; while an aged cool roof with albedo 0.45 and 0.56 will yield the annual savings by 5.12 kWh/m2 (15.4%) and 2.47 kWh/m2 (10.5%) in these two cities