A Study of Sustainable Social Housing Community Design in Britain and China

BritainandChinahaveexperiencedperiodsofrapidpopulationgrowthandinadequate housing construction. Social housing is a form of housing tenure easing the housing pressure. It solves residential demands of different living patterns in middle to low-income groups. The sustainable strategy lies in three aspects:1. Making the utmost use of the local natural environment;2. Providing reasonable public spaceandsuitabletraffic to revitalize community awareness; and 3. The holistic design of multiple dwelling units for different people and long-term needs. This paper shows two projects – Park Hill in Sheffield, UK and Longnan Garden in Shanghai – as precedents of how to design social housing with sustainable approaches by following the local natural characteristics,by respecting traditions and the different demands of residents and the long-term housing usage. UP TO HERE Compared with China’s 20-year social housing development, that in Britain has a long history and presents complicated multiplicities, could provide significant references. This paper shows that such communities could be design in steps: using the organic gallery apartment building layout, the special corridor system connecting the public function to neighborhoods, SI House theories optimizing the hostile design of dwelling units and components. During the design, the local nature and tradition should be respected. Specifically, the Park Hill is built up along the sloping field, four types of apartment units are based on the traditional terraced house, designed holistically for different families; the deck, which is called “street in the sky”, is not only the traffic but also the active place promoting public and neighborhoods relationships; the renovation design retains the former structure and makesthemaximizationofindoorflexibility.LongnanGardenissurroundedbyexisting resident districts; the organic planning based on the traditional courtyards ensures the enough sunlight and river views in the community; the community environment is improved by the courtyards,which include the ground are and roof gardens;elevated corridors run through courtyards connecting common rooms on the second floor; the 7.6-meter-heightskeletonisinnovatedfromSIhousingandtheexperienceofEuropean social housing. The paper summarizes the development tendency of social housing and provides reference for future

Bridge Diffusion Model: bridge non-English language-native text-to-image diffusion model with English communities

Text-to-Image generation (TTI) technologies are advancing rapidly, especially in the English language communities. However, English-native TTI models inherently carry biases from English world centric training data, which creates a dilemma for development of other language-native TTI models. One common choice is fine-tuning the English-native TTI model with translated samples from non-English communities. It falls short of fully addressing the model bias problem. Alternatively, training non-English language native models from scratch can effectively resolve the English world bias, but diverges from the English TTI communities, thus not able to utilize the strides continuously gaining in the English TTI communities any more. To build non-English language native TTI model meanwhile keep compatability with the English TTI communities, we propose a novel model structure referred as "Bridge Diffusion Model" (BDM). The proposed BDM employs a backbone-branch network structure to learn the non-English language semantics while keep the latent space compatible with the English-native TTI backbone, in an end-to-end manner. The unique advantages of the proposed BDM are that it's not only adept at generating images that precisely depict non-English language semantics, but also compatible with various English-native TTI plugins, such as different checkpoints, LoRA, ControlNet, Dreambooth, and Textual Inversion, etc. Moreover, BDM can concurrently generate content seamlessly combining both non-English native and English-native semantics within a single image, fostering cultural interaction. We verify our method by applying BDM to build a Chinese-native TTI model, whereas the method is generic and applicable to any other language