The construction and operation of highways has a significant impact on the environment. While such impact is impossible to avoid, modern highways are constructed and landscaped to minimise these impacts as far as possible. Good landscaping minimises the impact on those living or working close to the highway, while at the same time regenerating the natural landscape disturbed during construction. Using as its background the successful landscape design of the Nanjing-Hangzhou Expressway in Jiangsu Province, China, which opened to traffic in 2007, Highway Landscape Design includes reference to all aspects of the landscaping of highways, including interchanges, embankments, central reservations, bridges, service and toll station areas, and drainage systems. Appropriate consideration is given to the negative impact on the surrounding environment during the process of construction and it discusses the ecological evaluation and conservation strategy for the highway route. China is in some respects at the forefront of highway landscape design as a result of rapid growth and development coupled with the financial resources to implement major infrastructure works, and the concepts, technologies and methods developed for this Expressway provide valuable experience for sustainable development strategies for such infrastructure.

The Environment and Landscape in Motorway Design

Engineering & Transportation

Zhang, Min

Qian, Guochao

Tang, Shuyu

Jing, Chun

Engineering

Wiley/Blackwell

From the Back Cover This book introduces the point cloud; its applications in industry, and the most frequently used datasets. It mainly focuses on three computer vision tasks -- point cloud classification, segmentation, and registration -- which are fundamental to any point cloud-based system. An overview of traditional point cloud processing methods helps readers build background knowledge quickly, while the deep learning on point clouds methods include comprehensive analysis of the breakthroughs from the past few years. Brand-new explainable machine learning methods for point cloud learning, which are lightweight and easy to train, are then thoroughly introduced. Quantitative and qualitative performance evaluations are provided. The comparison and analysis between the three types of methods are given to help readers have a deeper understanding.With the rich deep learning literature in 2D vision, a natural inclination for 3D vision researchers is to develop deep learning methods for point cloud processing. Deep learning on point clouds has gained popularity since 2017, and the number of conference papers in this area continue to increase. Unlike 2D images, point clouds do not have a specific order, which makes point cloud processing by deep learning quite challenging. In addition, due to the geometric nature of point clouds, traditional methods are still widely used in industry. Therefore, this book aims to make readers familiar with this area by providing comprehensive overview of the traditional methods and the state-of-the-art deep learning methods.A major portion of this book focuses on explainable machine learning as a different approach to deep learning. The explainable machine learning methods offer a series of advantages over traditional methods and deep learning methods. This is a main highlight and novelty of the book. By tackling three research tasks -- 3D object recognition, segmentation, and registration using our methodology -- readers will have a sense of how to solve problems in a different way and can apply the frameworks to other 3D computer vision tasks, thus give them inspiration for their own future research. Numerous experiments, analysis and comparisons on three 3D computer vision tasks (object recognition, segmentation, detection and registration) are provided so that readers can learn how to solve difficult Computer Vision problems. Product Description This book introduces the point cloud; its applications in industry, and the most frequently used datasets. It mainly focuses on three computer vision tasks -- point cloud classification, segmentation, and registration -- which are fundamental to any point cloud-based system. An overview of traditional point cloud processing methods helps readers build background knowledge quickly, while the deep learning on point clouds methods include comprehensive analysis of the breakthroughs from the past few years. Brand-new explainable machine learning methods for point cloud learning, which are lightweight and easy to train, are then thoroughly introduced. Quantitative and qualitative performance evaluations are provided. The comparison and analysis between the three types of methods are given to help readers have a deeper understanding.With the rich deep learning literature in 2D vision, a natural inclination for 3D vision researchers is to develop deep learning methods for point cloud processing. Deep learning on point clouds has gained popularity since 2017, and the number of conference papers in this area continue to increase. Unlike 2D images, point clouds do not have a specific order, which makes point cloud processing by deep learning quite challenging. In addition, due to the geometric nature of point clouds, traditional methods are still widely used in industry. Therefore, this book aims to make readers familiar with this area by providing comprehensive overview of the traditional methods and the state-of-the-art deep learning methods.A m

3D Point Cloud Analysis: Traditional, Deep Learning, and Explainable Machine Learning Methods

Computers & Technology

Kuo, C.C. Jay

Liu, Shan

Kadam, Pranav

Computer Science

Springer

Foreign aid has connected China and the international community through many channels, and created new types of strong partnerships throughout the world. As a recipient country, China and donors have engaged in an unprecedentedly deep level of cooperation on development-related issues. China’s development experience has resulted in key changes to the relationships and partnerships between China and donors, from receiving foreign aid to entering into development cooperation. China has provided valuable experiences for other developing countries, experiences that are all the more relevant because they have revealed key factors at work in developing recipient countries. This has also led China to form closer cooperative relationships with other developing countries with regard to development issues. In short, foreign aid has changed China.

Foreign Aid in China

Business & Money

ZHOU, Hong

Zhang, Jun

Economics

love ring(Chinese Edition)

Shanghai Literature Art Publishing House Pub. Dat

Children without umbrellas must work hard(Chinese Edition)

Jilin Wenshi Publishing House

标准韩国语

安炳浩

孙鹤云

Linguistically Motivated Statistical Machine Translation: Models and Algorithms

Reference

Xiong, Deyi

Words, Language & Grammar

This book provides a wide variety of algorithms and models to integrate linguistic knowledge into Statistical Machine Translation (SMT). It helps advance conventional SMT to linguistically motivated SMT by enhancing the following three essential components: translation, reordering and bracketing models. It also serves the purpose of promoting the in-depth study of the impacts of linguistic knowledge on machine translation. Finally it provides a systematic introduction of Bracketing Transduction Grammar (BTG) based SMT, one of the state-of-the-art SMT formalisms, as well as a case study of linguistically motivated SMT on a BTG-based platform.

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