China's ambitious urbanization continues to provide a strong impetus for the construction industry to proliferate in the foreseeable future. While construction firms are supposed to contribute extra ...efforts to improve social welfare, they are also attempting to minimize their negative impacts on the environment. This has compounded the difficulty of fulfilling corporate social responsibility (CSR), and it is vitally important that CSR activities can be formulated accordingly. In this study, generic CSR activities were identified first through extensive literature review. Content analysis on CSR reports of construction firms and interviews with professionals were then conducted to make the generic CSR activities suit the Chinese construction industry. A questionnaire survey was finally adopted to collect professionals' opinions on the importance of CSR activities. It is found that the key factors or activity areas of CSR are environmental protection, construction quality and safety, community, employees, clients, and CSR management. The research findings suggest that contractors' CSR fulfillment should be embedded in the construction process as well as the uniqueness of construction practices in China.
Research into digital technology (DT) in construction practices has gained widespread attention. While the application of different DTs in facility management (FM) has been growing, to date, there is ...no holistic review of the various DT developments and research into FM. A total of 120 academic journal papers, conference proceedings and other technical notes published on the subject, mainly between 2004 and 2017, were reviewed in this paper. The applications of various major DTs, including 1) building information modelling (BIM), 2) reality capture technology (including 3D laser scanning, point cloud), 3) the Internet of Things (IoT) (including radio frequency identification (RFID) and sensor network technologies) and 4) geographic information system (GIS), were reviewed and scrutinised. The review identified a number of possibilities for future research into DT in FM, including, enhancing the interoperability of data, improving the accuracy of point cloud data for developing as-built models for existing facilities, and generating effective BIM/GIS asset database integration. It is hoped that this review and the future directions highlighted in this paper will assist researchers in identifying the areas where further research efforts are most required and in identifying which future directions would be most helpful for digital FM research.
•Application of various digital technologies on facilities management were examined•Interoperability of data from as-designed to as-built data remains a key barrier•More efforts on improving data capturing technologies for “as-is” BIM is needed•Future work should improve spatial and geometric aspects of GIS-BIM integration•Enhancing the capability of RFID-based data storage and management is required
Spintronics is an emergent interdisciplinary topic for the studies of spin-based, other than or in addition to charge-only-based physical phenomena. Since the discovery of giant magnetoresistance ...(GMR) effect in metallic multilayers, the first-generation spintronics has generated huge impact to the mass data storage industries. The second-generation spintronics, on the other hand, focuses on the integration of the magnetic and semiconductor materials and so to add new capabilities to the electronic devices. While spin phenomena have long been investigated within the context of conventional ferromagnetic materials, the study of spin generation, relaxation, and spin-orbit coupling in non-magnetic materials took off only recently with the advent of hybrid spintronics and it is here many novel materials and architectures can find their greatest potentials in both science and technology. This article reviews recent progress of the research on a selection of hybrid spintronic systems including those based on ferromagnetic metal (FM) and alloys, half-metallic materials, and two-dimensional (2D) materials. FM and alloys have spontaneous magnetization and usually high Curie temperature (Tc), half-metallic materials possess high spin polarization near the Fermi level (EF), and the 2D materials have unique band structures such as the Fermi Dirac cone and valley degree of freedom of the charge carriers. Enormous progress has been achieved in terms of synthesising the epitaxial hybrid spintronic materials and revealing their new structures and properties emerging from the atomic dimensions and the hetero-interfaces. Apart from the group-IV, III-V, and II-VI semiconductors and their nanostructures, spin injection and detection with 2D materials such as graphene, transition-metal dichalcogenides (TMDs) and topological insulators (TIs) has become a new trend and a particularly interesting topic due to either the long spin lifetime or strong spin-orbit coupling induced spin-momentum locking, which potentially leads to dissipationless electronic transport.
Computer vision (CV)-based technologies have been used to automate construction progress monitoring. The automation attempts to maximise precision and minimise human intervention in onsite progress ...monitoring. Such attempts have mainly focussed on exterior construction environments while there are significantly lesser number of studies on interior construction. This imbalance impedes automation of the onsite progress monitoring as a whole. Thus, the core intent of this study is to pave the way for advancing automated indoor progress monitoring by providing a systematic survey of extant literature. Main contributions of this survey include 1) presenting a full spectrum of CV-based approaches, tools, and algorithms adopted for indoor construction progress monitoring (ICPM) 2) portraying a succinct reference to the shortcomings, technical challenges, and scope limitations of the past studies on ICPM. The study then synthesises a readily usable agenda for hybridising CV with other data-driven technologies to improve automation in ICPM.
Display omitted
•Significant gap between indoor and outdoor construction in adopting computer vision.•Indoor progress monitoring is constrained due to object detection challenges.•These challenges are related to indoor objects, lighting conditions and camera movements.•Hybridising computer vision with other data-driven technologies is one of the future research directions.
The availability of innumerable intelligent building (IB) products, and the current dearth of inclusive building component selection methods suggest that decision makers might be confronted with the ...quandary of forming a particular combination of components to suit the needs of a specific IB project. Despite this problem, few empirical studies have so far been undertaken to analyse the selection of the IB systems, and to identify key selection criteria for major IB systems. This study is designed to fill these research gaps. Two surveys: a general survey and the analytic hierarchy process (AHP) survey are proposed to achieve these objectives. The first general survey aims to collect general views from IB experts and practitioners to identify the perceived critical selection criteria, while the AHP survey was conducted to prioritize and assign the important weightings for the perceived criteria in the general survey. Results generally suggest that each IB system was determined by a disparate set of selection criteria with different weightings. ‘Work efficiency’ is perceived to be most important core selection criterion for various IB systems, while ‘user comfort’, ‘safety’ and ‘cost effectiveness’ are also considered to be significant. Two sub-criteria, ‘reliability’ and ‘operating and maintenance costs’, are regarded as prime factors to be considered in selecting IB systems. The current study contributes to the industry and IB research in at least two aspects. First, it widens the understanding of the selection criteria, as well as their degree of importance, of the IB systems. It also adopts a multi-criteria AHP approach which is a new method to analyse and select the building systems in IB. Further research would investigate the inter-relationship amongst the selection criteria.
The Chinese government plans to adopt a low or no subsidy policy mechanism on renewable energy power development in the future. To achieve a balance between reducing financial burden on the ...government and ensuring profitability of investors as well as to account for the regional differences in China, a novel regional wind power grid feed-in tariff benchmark price mechanism by Net Present Value (NPV) method and Real Option (RO) method is proposed in this paper. The results voice support on the appropriateness of gradually decreasing the wind feed-in tariff (FIT) benchmark price to as low as the coal-fired FIT. The proposed FIT price level is presented as a price range on the basis of a guaranteed Internal Rate of Return (IRR) falls in between 8% to 15% for wind power investors. The results indicate that the current FIT price should be readjusted and redistributed. Although the FIT price in Central and South China grids is recommended to be relatively high, the NPV of wind farm project value in six regional grids are at the same level.
•A regional-power-grid-based wind FIT price mechanism is proposed.•Carbon emission trading scheme is considered under two scenarios.•Enterprise’s managerial flexibility and uncertainty is counted in the NPV model.•The calculation considers IRR ranges from 8% to 15%.•Policy implications are constructive for government and investors.
The construction industry has been criticised as one of the major greenhouse gas (GHG) emitters and a relatively unregulated sector in the management of carbon emissions. As the pressure on climate ...change related risks is mounting, a major cut in carbon emissions from construction operations is becoming a top priority if construction firms are to meet increasingly stringent emission controls. This study describes prototype architecture for implementing a carbon emission prediction and a simulation tool for construction projects using virtual prototyping technologies that is little investigated, analysed and modelled in the existing literature. The estimated emissions of the construction operations for each activity are calculated, tabulated and plotted to visually demonstrate the emission rates side by side with the integrated 4D models of the construction project. The presented virtual prototype (VP)-based model allows project teams to visualise the predicted emissions at different times in the construction processes, analyse the emission peaks, and allow the project team to take proactive measures against potential emissions. A real-life public housing construction project in Hong Kong is adopted to demonstrate the application of the emission prediction visualisation tool. By simulating likely carbon emissions during project planning phases in advance of actual construction activities, it is hoped that the tool can encourage exploration of possible strategies to minimize carbon emissions in construction sector.
Given the urgent need to enhance industry practices in a green, safe, and economical manner, facilitating the wider adoption of green procurement in building developments has been a major concern of ...the construction industry. This paper aims to provide insight into the factors that are important in enhancing green procurement in the construction process and to suggest recommendations for the effective adoption of green procurement through a questionnaire survey and expert interviews. The top three most significant factors identified are mandatory environmental regulations by the government, client requirements in tendering, and government and non-governmental organization requirements. The results of a factor analysis of 35 variables identify 10 underlying grouped factors for facilitating effective green procurement in Hong Kong's construction industry. The factor group “Regulations and standards of green procurement by the government” is the most significant, followed by “Life-cycle considerations and green construction technology” and “Executive management's commitments and requirements.” Efforts or initiatives undertaken by the community and the government on green procurement, such as competitions/awards, incentive schemes, and executives' green procurement commitments and requirements, are considered important in the green procurement process. The experts interviewed indicated that the government should take a proactive role in pushing green procurement adoption. Advanced construction IT (e.g., BIM) should be employed to stimulate the construction process to incorporate a green design approach and reduce waste. In addition, the establishment of a fully functioning green material market would help to promote the concept of green procurement and gradually lower material costs. Active engagement of suppliers to provide the performance details of construction materials is also necessary.
•Mandatory environmental regulation is key driver for green procurement adoption.•Active engagement of suppliers to provide material performance details is needed.•The depth and liability of materials in green labelling system should be enhanced.•Construction contract should encourage the use of more green or reusable materials.
The management of unruptured brain arteriovenous malformations (ubAVMs) remains controversial despite ARUBA trial (A Randomized Trial of Unruptured Brain Arteriovenous Malformation), a controlled ...trial that suggested superiority of conservative management over intervention. However, microsurgery occurred in only 14.9% of ARUBA intervention cases, raising concerns about the study's generalizability. Our purpose was to evaluate whether, in a larger ARUBA-eligible ubAVM population, microsurgery produces acceptable outcomes.
Demographic data, AVM characteristics, and treatment outcomes were evaluated in 155 ARUBA-eligible bAVMs treated with microsurgery between 1994 and 2014. Outcomes were rates of early disabling deficits and permanent disabling deficits with modified Rankin Scale score ≥3 or any permanent neurological deficits with modified Rankin Scale score ≥1. Covariates associated with outcomes were determined by regression analysis.
Of 977 AVM patients, 155 ARUBA-eligible patients had microsurgical resection (71.6% surgery only and 25.2% with preoperative embolization). Mean follow-up was 36.1 months. Complete obliteration was achieved in 94.2% after initial surgery and 98.1% on final angiography. Early disabling deficits and permanent disabling deficits occurred in 12.3% and 4.5%, respectively, whereas any permanent neurological deficit (modified Rankin Scale score ≥1) occurred in 16.1%. Among ubAVM of Spetzler-Martin grades 1 and 2, complete obliteration occurred in 99.2%, with early disabling deficits and permanent disabling deficits occurring in 9.3% and 3.4%, respectively. Major bleeding was the only significant predictor of early disabling deficits on multivariate analysis (P<0.001).
Microsurgery in this cohort produced less disabling deficits than ARUBA with similar morbidity and AVM obliteration as other cohort series. This disparity between our results and ARUBA suggests that future controlled trials should focus on the safety and efficacy of microsurgery with or without adjunctive embolization in carefully selected ubAVM patients.
The malfunctioning of the heating, ventilating, and air conditioning (HVAC) system is considered to be one of the main challenges in modern buildings. Due to the complexity of the building management ...system (BMS) with operational data input from a large number of sensors used in HVAC system, the faults can be very difficult to detect in the early stage. While numerous fault detection and diagnosis (FDD) methods with the use of statistical modeling and machine learning have revealed prominent results in recent years, early detection remains a challenging task since many current approaches are unfeasible for diagnosing some HVAC faults and have accuracy performance issues. In view of this, this study presents a novel hybrid FDD approach by combining random forest (RF) and support vector machine (SVM) classifiers for the application of FDD for the HVAC system. Experimental results demonstrate that our proposed hybrid random forest-support vector machine (HRF-SVM) outperforms other methods with higher prediction accuracy (98%), despite that the fault symptoms were insignificant. Furthermore, the proposed framework can reduce the significant number of sensors required and work well with the small number of faulty training data samples available in real-world applications.
PDF
