In this paper, Macau Taipa Village, a historical district in an island-type city, is the research focus, and a parametric design-based method for designing historical districts is proposed. First, the shape and distribution of roads in historical districts is studied through on-the-spot investigation and measurement and data are collected on the width, depth, and area of street blocks, average street length and width, street orientation, building width, depth, acreage, and height, and building orientation. Second, the acquired data are transmitted to the Grasshopper parameterization platform, and an intelligently generated program produces calculations. Through multiple iterations and evaluations of genetic algorithms based on the needs of modern urban design and planning constraints, the building density is further reduced, and more landscape areas are added. The parametric model is optimized to gradually generate the urban spatial design that meets contemporary requirements. The research reveals that (1) the grasshopper algorithm’s generated block design inherits the characteristics of the conventional historical block. (2) The historical block where the data were collected on site and the block where Grasshopper is applied should maintain the consistency of the regional context. (3) This method can be applied to the design of new urban areas, and the scope of application can be further adjusted through collaboration and the needs of the owners at a later stage.

本文对寒冷地区某高校一栋教学楼进行温湿度实测，并通过问卷对教室的热、声环境进行使用后评价，实测温度表明，多数教室基本达不到18℃，湿度也较低。主观问卷结果表明，与温度满意度相比，学生对噪声的满意度更低，消极影响更多。

Different from the existing empirical landscape measurement methods, this article explores an effective method to quantify the landscape through the use of computer vision perception. First, based on image semantic segmentation technology, a large number of excellent case images are put into image semantic segmentation and annotation tools for image segmentation. Secondly, the image semantic segmentation is used to quantitatively analyze the landscape space elements of the old urban site, and obtain the data value of each landscape element in the excellent case, which provides a reference for the design of the element ratio data basis. Finally, it is applied to the street space in the old city of Macau to perform a quantitative analysis of the computer vision perception of the streets in the old city. Get quantitative suggestions for landscape improvement, and provide new methods for quantitative research and transformation of old urban areas. 

本研究将专业色卡与高效软件色彩识别相结合，提出了一种新的可量化、精细化的城市街道色彩分析方法，解决了城市色彩研究分析量化效率低、难度大的问题。 研究主要利用中国建筑色卡（CBCC）和Python（使用图片的HSV颜色分割程序）等软件对街景进行颜色识别。 本文从街道立面的色彩构成、类型、比例、视觉层次、色彩顺序等方面，对澳门新马路的色彩进行多角度的定量分析。 将色卡比色法与计算机颜色识别相结合的方法，不仅考虑了建筑物固有的颜色，还考虑了环境影响下的颜色情况，可以更完整地表达建筑物的“实际颜色情况”。 本文对建筑色彩和环境色彩进行了全面的量化、梳理、总结和比较。 该方法在实践中具有良好的普适性和易用性，研究结论可为澳门色彩规划提供参考，对城市更新的色彩选择具有参考意义，为城市色彩研究提供新方法 。

岭南建筑是中国古典建筑流派类型的重要组成之一，作为最具岭南特色的岭南建筑屋面，其保留与修缮技术尤为重要。本文以岭南古建屋面之瓦片与排水修缮技术为主要研究对象，从岭南环境特点为背景，通过梳理屋面瓦片形态与材质类型、分析屋面铺瓦形式与屋面排水之间的关系、补充传统瓦片制作工艺等方面的研究分析，总结出较为有效的屋面修缮技术，为岭南古建筑屋面修缮提供可实施性的应用参考。

岭南历史建筑中随处可见彩色玻璃的应用，尤其是在需要大面积采光的门窗位置会使用一种独特的艺术玻璃花窗作为通风采光之用，被称为满洲窗。本文从岭南地区彩色玻璃使用的历史为背景，首先梳理广州地区彩色玻璃类型与工艺发展。其次，归纳蚀刻玻璃画的制作过程。再次，通过在岭南历史建筑满洲窗中的使用，挖掘彩色玻璃在满洲窗中的应用规律。最后得出彩色玻璃在满洲窗中应用的基本组合方式。这些规律与方式不仅可为岭南历史建筑的修缮提供参考，也可以为现代建筑的开窗形式与艺术化营造提供新的启发。

The Shanhaiguan Great Wall is a section of the Great Wall of the Ming Dynasty, which is a UNESCO World Heritage Site. Both sides of its basic structure are composed of rammed earth and gray bricks. The surface gray bricks sustain damage from environmental factors, resulting in a decline in their structural quality and even a threat to their safety. Traditional surface damage detection methods rely primarily on manual identification or manual identification following unmanned aerial vehicle (UAV) aerial photography, which is labor-intensive. This paper applies the YOLOv4 machine learning model to the gray surface bricks of the Plain Great Wall of Shanhaiguan as an illustration. By slicing and labeling the photos, creating a training set, and then training the model, the proposed approach automatically detects four types of damage (chalking, plants, ubiquinol, and cracking) on the surface of the Great Wall. This eliminates the need to expend costly human resources for manual identification following aerial photography, thereby accelerating the work. Through research, it is found that (1) compared with manual detection, this method can quickly and efficiently monitor a large number of wall samples in a short period of time and improve the efficiency of brick wall detection in ancient buildings. (2) Compared with previous approaches, the accuracy of the current method is improved. The identifiable types are increased to include chalking and ubiquinol, and the accuracy rate increases by 0.17% (from 85.70% before to 85.87% now). (3) This method can quickly identify the damaged parts of the wall without damaging the appearance of the historical building structure, enabling timely repair measures.

With the rapid growth of global urbanization and the rising demand for sustainable development, it is essential to study the performance and durability of building materials. As a traditional and widely employed building material, Chinese clay tiles play a significant role in traditional Chinese architecture. However, traditional methods for assessing structural surface damage necessitate the time-consuming and labor-intensive assessment and judgment of trained professionals. Consequently, it is crucial to employ machine learning techniques for automatic damage type identification. This study identifies the types of damage to Chinese clay tiles in Macau by employing machine learning techniques and the YOLOv4 object detection model. A total of 363 photographs of on-site Chinese clay tiles were used as training samples, and 200 epochs of the model training were performed. The primary findings of this study are as follows: (1) The machine learning method, based on the YOLOv4 model, provides an effective and precise solution for the automatic identification of Chinese clay tiles damage types, overcoming the human and time-cost constraints of conventional evaluation methods. (2) The detection accuracy of the detection model in this study is 95.42% for the detection of Chinese clay tiles cracks, 80.91% for the detection of stains, and 89.34% for the detection of surface wear, with an overall accuracy of 88.98%, which meets the basic detection requirements. (3) The experimental results demonstrate the viability and efficacy of the proposed method for identifying clay tile damage types and provide a method reference for the preservation and sustainable development of historical buildings.

郑亮和陈以乐合作撰写的论文题为《澳门遗产的语境研究——以澳门葡京酒店为例》，在《 中国艺术设计年鉴 》的理论研究卷中荣获了一等奖。他们的研究引人入胜地探索了澳门葡京酒店作为一项重要遗产的背景和语境。通过详细的调查和分析，他们揭示了澳门葡京酒店的历史背景、文化价值和建筑特色，并深入探讨了其在澳门遗产保护与传承中的重要作用。

文章基于当前热议的”地摊经济”背景,通过考察摆摊最为密集的澳门历史城区,探讨澳门特别行政区 摆摊设施 或临时性建筑的类型,从澳门摆摊的由来、澳门对小摊贩的城市管理条例、摆摊设施或临时性建筑与城市公共空间的关系等内容来阐述当前澳门摆摊的需求功能与市井文化之间的关系,并结合澳门摆摊经济的现状,提出具有可行性的经济复苏措施与建议,同时提升人们对目前澳门摆摊设施或临时性建筑与城市公共空间活力及文化保护的关注。