Modeling dynamic construction work template from existing scheduling records via sequential machine learning

Today, construction planning and scheduling is almost always performed manually, by experienced practitioners. The knowledge of those individuals is materialized, maintained, and propagated through master schedules and look-ahead plans. While historical project schedules are available, manually mining their embedded knowledge to create generic work templates for future projects or revising look-ahead schedules is very difficult, time-consuming and error-prone. The rigid work templates from prior research are also not scalable to cover the inter and intra-class variability in historical schedule activities. This paper aims at fulfilling these needs via a new method to automatically learn construction knowledge from historical project planning and scheduling records and digitize such knowledge in a flexible and generalizable data schema. Specifically, we present Dynamic Process Templates (DPTs) based on a novel vector representation for construction activities where the sequencing knowledge is modeled with generative Long Short-Term Memory Recurrent Neural Networks (LSTM-RNNs). Our machine learning models are exhaustively tested and validated on a diverse dataset of 32 schedules obtained from real-world projects. The experimental results show our method is capable of learning planning and sequencing knowledge at high accuracy across different projects. The benefits for automated project planning and scheduling, schedule quality control, and automated generation of project look-aheads are discussed in detail.     

城市水循环演变及对策分析

全球气候变化和快速城市化改变了自然水循环过程,使水循环呈现"自然-社会"二元特征。城市是二元水循环耦合程度最深的区域,城市水循环的驱动力、结构与过程呈现复杂化,由此引发的城市水问题越来越突出,未来城市水循环面临严峻挑战。本文在识别城市水循环的演变历程和机理的基础上,解析了城市水问题的产生根源。以城市水问题以及未来城市水循环发展趋势为导向,提出了未来城市水循环调控的总体思路,论述了未来城市水循环调控的"理水""用水""治水""管水"四大战略,阐明了以"安""和""畅""保""节""回""净""智"八字方针为指导的未来城市水循环调控实现途径。     

城市河流系统治理策略在鹅颈水生态修复中的应用

在简要介绍城市河流系统治理策略的基础上，详细论述其在鹅颈水生态修复中的应用。鹅颈水治理以流域为空间单位，准确把握河流主要问题，综合考量水资源、水安全、水环境、水生态、水文化，坚持工程和非工程措施并重，分阶段逐步实现洪水风险管理、外源污染控制、河流水质修复、河流生态系统恢复的目标。结果表明，鹅颈水目前已基本消除黑臭，水质逐渐提升至国家地表水Ⅳ类水标准。提出进一步加强河流生态系统恢复、优化管理制度、逐步建立全过程和全指标生态监测评估体系、实施弹性管理等鹅颈水系统治理措施。     

数字技术环境下景观规划设计教学改革与实践

设计创新能力培养已成为21世纪风景园林学规划设计教学核心，在此背景下，由知识传输导向的教学模式正逐步转变为由设计与科研并肩引领知识增长的教学模式，数字化景观规划设计教学体系与方法成为当代风景园林教育亟待充实并应用的重要内容。立足风景园林教学前沿，基于对当代风景园林规划设计教育的系统把握，以东南大学风景园林专业教学实践为例，提出整合数字景观技术平台，构建“浸入式”数字技术教学环境，实现数字平台与教学体系的协同创新；继而针对传统教学方法局限，利用数字化教学平台进行“耦合教学法”创新实践，加强实证性知识体系集成融合，实现风景园林规划设计课程教学模式的系统探索与实践。     

基于移动窗口法的城市遥感生态质量评价研究

为进一步提高城市生态监测的精确度，在前人开展的城市生态遥感监测研究的基础上引入“区域尺度”的概念，充分考虑小区域范围内不同地物间的交互作用，并利用移动窗口模型(Moving Window-Remote Sensing Ecology Index, MW-RSEI)对沈阳市浑南区的遥感影像进行逐像元分析。实验结果表明，MW-RSEI模型和生态遥感监测模型（Remote Sensing Ecology Index, RSEI)在整体生态评价趋势上表现出一致性。但MW-RSEI模型对城市生态中的细节区域表征更明显。考虑到建筑及裸地周围植被的影响，其较差生态区域的占比仅为6%，生态评价为优的区域占比为11%。研究区生态评价结果表现得较为连续，并未出现明显的断层现象。该结果具有现实意义且与实际生态分布更为符合。MW-RSEI模型在城市生态监测中更为适用，可为相关部门提供一定的技术参考。     

Engineering knowledge formalization and proposition for informatics development towards a CAD-integrated DfX system for product design

Target design methodologies (DfX) were developed to cope with specific engineering design issues such as cost-effectiveness, manufacturability, assemblability, maintainability, among others. However, DfX methodologies are undergoing the lack of real integration with 3D CAD systems. Their principles are currently applied downstream of the 3D modelling by following the well-known rules available from the literature and engineers’ know-how (tacit internal knowledge).This paper provides a method to formalize complex DfX engineering knowledge into explicit knowledge that can be reused for Advanced Engineering Informatics to aid designers and engineers in developing mechanical products. This research work wants to define a general method (ontology) able to couple DfX design guidelines (engineering knowledge) with geometrical product features of a product 3D model (engineering parametric data). A common layer for all DfX methods (horizontal) and dedicated layers for each DfX method (vertical) allow creating the suitable ontology for the systematic collection of the DfX rules considering each target. Moreover, the proposed framework is the first step for developing (future work) a software tool to assist engineers and designers during product development (3D CAD modelling).A design for assembly (DfA) case study shows how to collect assembly rules in the given framework. It demonstrates the applicability of the CAD-integrated DfX system in the mechanical design of a jig-crane. Several benefits are recognized: (i) systematic collection of DfA rules for informatics development, (ii) identification of assembly issues in the product development process, and (iii) reduction of effort and time during the design review.     

More than bin packing: Dynamic resource allocation strategies in cloud data centers

Resource allocation strategies in virtualized data centers have received considerable attention recently as they can have substantial impact on the energy efficiency of a data center. This led to new decision and control strategies with significant managerial impact for IT service providers. We focus on dynamic environments where virtual machines need to be allocated and deallocated to servers over time. Simple bin packing heuristics have been analyzed and used to place virtual machines upon arrival. However, these placement heuristics can lead to suboptimal server utilization, because they cannot consider virtual machines, which arrive in the future. We ran extensive lab experiments and simulations with different controllers and different workloads to understand which control strategies achieve high levels of energy efficiency in different workload environments. We found that combinations of placement controllers and periodic reallocations achieve the highest energy efficiency subject to predefined service levels. While the type of placement heuristic had little impact on the average server demand, the type of virtual machine resource demand estimator used for the placement decisions had a significant impact on the overall energy efficiency.     

Rapidly finding CAD features using database optimization

Automatic feature recognition aids downstream processes such as engineering analysis and manufacturing planning. Not all features can be defined in advance; a declarative approach allows engineers to specify new features without having to design algorithms to find them. Naive translation of declarations leads to executable algorithms with high time complexity. Database queries are also expressed declaratively; there is a large literature on optimizing query plans for efficient execution of database queries. Our earlier work investigated applying such technology to feature recognition, using a testbed interfacing a database system (SQLite) to a CAD modeler (CADfix). Feature declarations were translated into SQL queries which are then executed.The current paper extends this approach, using the PostgreSQL database, and provides several new insights: (i) query optimization works quite differently in these two databases, (ii) with care, an approach to query translation can be devised that works well for both databases, and (iii) when finding various simple common features, linear time performance can be achieved with respect to model size, with acceptable times for real industrial models. Further results also show how (i) lazy evaluation can be used to reduce the work performed by the CAD modeler, and (ii) estimating the time taken to compute various geometric operations can further improve the query plan. Experimental results are presented to validate our main conclusions.     

土地利用规划的范式转变——基于生态伦理的横断面规划思想的引介

横断面规划的思想源于广阔的区域性议题及可持续发展理念,是应对生态环境问题的一种综合性的规划方法。横断面规划的基础是地理景观,地理景观反映了人与自然的关系,城乡横断面表现了人与自然关系的梯度。基于横断面的形态分类体现了人地关系的刻度,将发展目标转译为某一种形态实质是规定某一种具体的人地关系,是生态伦理价值的具体表现。以横断面分区取代功能分区,把规划调查、分析、设计和开发控制有效地整合在一起,实现了土地利用规划的范式转变。     

An optimal motion planning method for computer-assisted surgical training

This paper focuses on the development and validation of an optimal motion planning method for computer-assisted surgical training. The context of this work is the development of new-generation systems that combine artificial intelligence and computer vision techniques in order to adjust the learning process to specific needs of a trainee, while preventing a trainee from the memorization of particular task settings. The problem described in the paper is the generation of shortest, collision-free trajectories for laparoscopic instrument movements in the rigid block world used for hand–eye coordination tasks. Optimal trajectories are displayed on a monitor to provide continuous visual guidance for optimal navigation of instruments. The key result of the work is a framework for the transition from surgical training systems in which users are dependent on predefined task settings and lack guidance for optimal navigation of laparoscopic instruments, to the so called intelligent systems that can potentially deliver the utmost flexibility to the learning process. A preliminary empirical evaluation of the developed optimal motion planning method has demonstrated the increase of total scores measured by total time taken to complete the task, and the instrument movement economy ratio. Experimentation with different task settings and the technical enhancement of the visual guidance are subjects of future research.