Project Controls and Management Systems : current practice and how it has changed over the past decade

Project Controls and Management System (PCMS) refers to an ecosystem of processes, tools and personnel required for the proper planning and execution of capital projects throughout the different phases of design, procurement, construction and startup. This can be divided into different focus areas (functions) that would include Estimating, Planning, Scheduling, Cost Control, Change Management, Progressing, and Forecasting. Various trends such as globalization, contractor specialization and information technology developments have impacted the way PCMS are implemented and made it the subject of extensive research over the past years to investigate how to best utilize those trends. Replicating the research methodology used in a 2011 report published by the Construction Research Institute (CII), this work aims to investigate the current status of PCMS implementation and how it has changed over the past decade. It was concluded that while the original PCMS principles are still valid, adoption has drastically changed in terms of efficiency for the majority of the functions. The research also identifies areas of potential concerns and provides recommendations for further improvement.Civil, Architectural, and Environmental Engineerin

Adaptive Consistency Guarantees for Large-Scale Replicated Services

To maintain consistency, designers of replicated services have traditionally been forced to choose from either strong consistency guarantees or none at all. Realizing that a continuum between strong and optimistic consistencies is semantically meaningful for a broad range of network services, previous research has proposed a continuous consistency model for replicated services to support the tradeoff between the guaranteed consistency level, performance and availability. However, to meet changing application needs and to make the model useful for interactive users of large-scale replicated services, the adaptability and the swiftness of inconsistency resolution are important and challenging. This paper presents IDEA (an Infrastructure for DEtection-based Adaptive consistency guarantees) for adaptive consistency guarantees of large-scale, Internet-based replicated services. The main functions enabled by IDEA include quick inconsistency detection and resolution, consistency adaptation and quantified consistency level guarantees. Through experimentation on the Planet-Lab, IDEA is evaluated from two aspects: its adaptive consistency guarantees and its performance for inconsistency resolution. Results show that IDEA is able to provide consistency guarantees adaptive to user’s changing needs, and it achieves low delay for inconsistency resolution and incurs small communication overhead

Applying autonomy to distributed satellite systems: Trends, challenges, and future prospects

While monolithic satellite missions still pose significant advantages in terms of accuracy and operations, novel distributed architectures are promising improved flexibility, responsiveness, and adaptability to structural and functional changes. Large satellite swarms, opportunistic satellite networks or heterogeneous constellations hybridizing small-spacecraft nodes with highperformance satellites are becoming feasible and advantageous alternatives requiring the adoption of new operation paradigms that enhance their autonomy. While autonomy is a notion that is gaining acceptance in monolithic satellite missions, it can also be deemed an integral characteristic in Distributed Satellite Systems (DSS). In this context, this paper focuses on the motivations for system-level autonomy in DSS and justifies its need as an enabler of system qualities. Autonomy is also presented as a necessary feature to bring new distributed Earth observation functions (which require coordination and collaboration mechanisms) and to allow for novel structural functions (e.g., opportunistic coalitions, exchange of resources, or in-orbit data services). Mission Planning and Scheduling (MPS) frameworks are then presented as a key component to implement autonomous operations in satellite missions. An exhaustive knowledge classification explores the design aspects of MPS for DSS, and conceptually groups them into: components and organizational paradigms; problem modeling and representation; optimization techniques and metaheuristics; execution and runtime characteristics and the notions of tasks, resources, and constraints. This paper concludes by proposing future strands of work devoted to study the trade-offs of autonomy in large-scale, highly dynamic and heterogeneous networks through frameworks that consider some of the limitations of small spacecraft technologies.Postprint (author's final draft

DECISION MAKING PROCESSES FOR BIM SOFTWARE SELECTION IN THE U.S. A.E.C. INDUSTRY: DEVELOPING A UNIFIED, STREAMLINED FRAMEWORK.

The use of Building Information Modeling (BIM) techniques and tools continues to gain popularity in the Architecture, Engineering and Construction (AEC) industry as more companies in the various sectors are utilizing it in one form or another. In this research, the decision-making process of construction firms with respect to the selection of BIM software for use is investigated. Through one on one interviews and gathered survey responses, a framework mapping out the various paths the exist in the decision-making process are explored. This data is then used to form a framework for BIM software selection in the construction sector of the AEC industry in the United States

CBR and MBR techniques: review for an application in the emergencies domain

The purpose of this document is to provide an in-depth analysis of current reasoning engine practice and the integration strategies of Case Based Reasoning and Model Based Reasoning that will be used in the design and development of the RIMSAT system. RIMSAT (Remote Intelligent Management Support and Training) is a European Commission funded project designed to: a.. Provide an innovative, 'intelligent', knowledge based solution aimed at improving the quality of critical decisions b.. Enhance the competencies and responsiveness of individuals and organisations involved in highly complex, safety critical incidents - irrespective of their location. In other words, RIMSAT aims to design and implement a decision support system that using Case Base Reasoning as well as Model Base Reasoning technology is applied in the management of emergency situations. This document is part of a deliverable for RIMSAT project, and although it has been done in close contact with the requirements of the project, it provides an overview wide enough for providing a state of the art in integration strategies between CBR and MBR technologies.Postprint (published version

Building Information Modelling (BIM) aided waste minimisation framework

Building design can have a major impact on sustainability through material efficiency and construction waste minimisation (CWM). The construction industry consumes over 420 million tonnes of material resources every year and generates 120 million tonnes of waste containing approximately 13 million tonnes of unused materials. The current and on-going field of CWM research is focused on separate project stages with an overwhelming endeavour to manage on-site waste. Although design stages are vital to achieve progress towards CWM, currently, there are insufficient tools for CWM. In recent years, Building Information Modelling (BIM) has been adopted to improve sustainable building design, such as energy efficiency and carbon reduction. Very little has been achieved in this field of research to evaluate the use of BIM to aid CWM during design. However, recent literature emphasises a need to carry out further research in this context. This research aims to investigate the use of BIM as a platform to help with CWM during design stages by developing and validating a BIM-aided CWM (BaW) Framework. A mixed research method, known as triangulation, was adopted as the research design method. Research data was collected through a set of data collection methods, i.e. selfadministered postal questionnaire (N=100 distributed, n=50 completed), and semistructured follow-up interviews (n=11) with architects from the top 100 UK architectural companies. Descriptive statistics and constant comparative methods were used for data analysis. The BaW Framework was developed based on the findings of literature review, questionnaire survey and interviews. The BaW Framework validation process included a validation questionnaire (N=6) and validation interviews (N=6) with architects. Key research findings revealed that: BIM has the potential to aid CWM during design; Concept and Design Development stages have major potential in helping waste reduction through BIM; BIM-enhanced practices (i.e. clash detection, detailing, visualisation and simulation, and improved communication and collaboration) have impacts on waste reduction; BIM has the most potential to address waste causes (e.g. ineffective coordination and communication, and design changes); and the BaW Framework has the potential to enable improvements towards waste minimisation throughout all design stages. Participating architects recommended that the adoption of the BaW Framework could enrich both CWM and BIM practices, and most importantly, would enhance waste reduction performance in design. The content should be suitable for project stakeholders, architects in particular, when dealing with construction waste and BIM during design

High-Resolution Deep Image Matting

Image matting is a key technique for image and video editing and composition. Conventionally, deep learning approaches take the whole input image and an associated trimap to infer the alpha matte using convolutional neural networks. Such approaches set state-of-the-arts in image matting; however, they may fail in real-world matting applications due to hardware limitations, since real-world input images for matting are mostly of very high resolution. In this paper, we propose HDMatt, a first deep learning based image matting approach for high-resolution inputs. More concretely, HDMatt runs matting in a patch-based crop-and-stitch manner for high-resolution inputs with a novel module design to address the contextual dependency and consistency issues between different patches. Compared with vanilla patch-based inference which computes each patch independently, we explicitly model the cross-patch contextual dependency with a newly-proposed Cross-Patch Contextual module (CPC) guided by the given trimap. Extensive experiments demonstrate the effectiveness of the proposed method and its necessity for high-resolution inputs. Our HDMatt approach also sets new state-of-the-art performance on Adobe Image Matting and AlphaMatting benchmarks and produce impressive visual results on more real-world high-resolution images.Comment: AAAI 202