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This paper analyzes the data of this year's athletes' physical fitness test scores and manages the classification of different physical qualities of the farmer. In order to reduce the manual calculation and increase the prediction efficiency, as well as to unify the scoring criteria of previous years, this paper proposes a comprehensive performance prediction model based on deep neural network algorithm. First, principal component analysis is used to transform multiple attributes with strong correlation into independent attributes that are not related to each other, and to reduce the time and space for model training by eliminating redundancy. Second, a back propagation (BP) neural network algorithm is used to build a physical fitness test prediction model, and the model is applied to the test dataset for model performance evaluation. Finally, the physical fitness test model was applied to other years for comprehensive performance prediction, and the differences between the model prediction results and the actual teachers' manual calculation results were observed. The results showed very good prediction results for 2021, in which 92.95% of the data had an absolute value of error less than 2 and only 0.06% had an absolute value of error greater than 4, which indicated that the prediction performance of the model was extremely significant. At the same time, a new athletic athletic scoring standard was also developed based on the neural network BP model to provide a more scientific theoretical basis and guidance for the evaluation of athletic ability of athletes.

This article reports on the design, modeling, control, and testing of a novel compliant nanopositioning stage driven by a self-developed normal-stressed electromagnetic actuator. To facilitate the parameter selection for the stage to achieve the desired stroke and natural frequency, an analytical model of both the electromagnetic circuit and flexure mechanism is established, which is then systematically verified through finite element analysis. By combining a proportional--integral--differential (PID)-based main controller with a system dynamics inversion-based feedforward compensator, a closed-loop control system for the stage is constructed with the main controller being tuned through Bode's ideal transfer function-based loop-shaping method. The experimental result shows that a stroke of ± 95 μ m and a first natural frequency of 743 Hz are achieved for the designed stage. Finally, taking advantage of the constructed control system, the nanopositioning capability is demonstrated by finely tracking the harmonic and nanostair commands.

PurposeThe practice of facility management (FM) has been evolving with the rapid development of pervasive sensing technologies (PSTs) such as sensors, automatic identification (auto-ID), laser scanning and photogrammetry. Despite the proliferation of research on the use of PSTs for FM, a comprehensive review of such research is missing from the literature. This study aims to cover the knowledge void by examining the status quo and challenges of the selected PSTs with a focus on FM.Design/methodology/approachThis paper reviewed 204 journal papers recounting cases of using PSTs for FM. The reviewed papers were extracted from Elsevier Scopus database using the advanced search.FindingsFindings of this study revealed that PSTs and FM applications form a many-to-many mapping, i.e. one PST could facilitate many FM applications, and one application can also be supported by various PSTs. It is also found that energy modeling and management is the most referred purpose in FM to adopt PSTs, while space management, albeit important, received the least attention. Five challenges are identified, which include high investment on PSTs, data storage problem, absence of proper data exchange protocols for data interoperability, a lack of mature data processing methods for data utilization and privacy of users.Originality/valueThis paper paints a full picture of PSTs adoption for FM. It pinpoints the promising explorations for tackling the key challenges to future development.

The elevation of atmospheric CO2 is an inevitable trend that would lead to significant impact on the interrelated carbon and nitrogen cycles through microbial activities in the aquatic ecosystem. Eutrophication has become a common trophic state of inland waters throughout the world, but how the elevated CO2 affects N cycles in such eutrophic water with algal bloom, and how vegetative restoration helps to mitigate N2O emission remains unknown. We conducted the experiments to investigate the effects of ambient and elevated atmospheric CO2 (a[CO2], e[CO2]; 400, 800 μmol﹒mol−1) with and without the floating aquatic plant, Eichhornia crassipes (Mart.) Solms, on N-transformation in eutrophic water using the 15N tracer method. The nitrification could be slightly inhibited by e[CO2], due mainly to the competition for dissolved inorganic carbon between algae and nitrifiers. The e[CO2] promoted denitrification and N2O emissions from eutrophic water without growth of plants, leading to aggravation of greenhouse effect and forming a vicious cycle. However, growth of the aquatic plant, Eichhornia crassipes, slightly promoted nitrification, but reduced N2O emissions from eutrophic water under e[CO2] conditions, thereby attenuating the negative effect of e[CO2] on N2O emissions. In the experiment, the N transformation was influenced by many factors such as pH, DO and algae density, except e[CO2] and plant presence. The pH could be regulated through diurnal photosynthesis and respiration of algae and mitigated the acidification of water caused by e[CO2], leading to an appropriate pH range for both nitrifying and denitrifying microbes. Algal respiration at night could consume DO and enhance abundance of denitrifying functional genes (nirK, nosZ) in water, which was also supposed to be a critical factor affecting denitrification and N2O emissions. This study clarifies how the greenhouse effect caused by e[CO2] mediates N biogeochemical cycle in the aquatic ecosystem, and how vegetative restoration mitigates greenhouse gas emission.

Occupational health and safety (OHS) is of the utmost concern in the construction sector. For decades, researchers and practitioners have endeavoured to enhance construction OHS performance through various measures ranging from “hard” technologies (in this paper, the “first wave” of construction OHS management) such as provision of personal protective equipment, to the more recent “soft”, managerial approaches (the “second wave”) such as fostering a safety culture. Although considerable improvements have been made in construction OHS, the general sentiment is that construction remains one of the most dangerous sectors, warranting more innovative or even revolutionary approaches. This research seeks to develop a smart construction object (SCO)-enabled OHS management system. The central tenet of the system is that artificial intelligence (AI), as the art of creating machines that perform functions that require intelligence when performed by people, represents a direction of the “third wave” in construction OHS management. The system embraces emergent SCOs and harnesses the power of their smart properties of awareness, communicativeness, and autonomy. The system is demonstrated and validated in real-life construction practice and a controlled lab test with a tower crane, the cause of many construction-related injuries and fatalities, as the subject. It is found that the SCO-enabled OHS management system can identify dangerous situations and respond to them autonomously. This research suggests that smarter construction, through incorporation of AI in particular, is a direction of much promise in terms of improving construction OHS.

The Architecture, Engineering, construction, and operation (AECO) industry has been strenuously exploring smart technologies to solve its many chronic problems. Smart construction object (SCO) is proposed as a step towards ubiquitous computing and smartness in the construction context. SCOs are defined as construction resources made ‘smart’ by augmenting them with awareness, communicativeness, and autonomy. SCOs will lead to a new paradigm of smart construction. In the meantime, cognitive facility management (FM) is proposed as a step towards active intelligence of FM. It can perceive through cognitive systems, learn in the manner of human cognition with the power of cognitive computing to improve the quality of people’s life and productivity of core business. The design of cognitive FM is to apply CIoT to FM with the consideration of integrating its cyber, physical, social systems (i.e., cyber-physical-social system, CPSS). In this chapter, a framework of cognitive FM is introduced, with eight layers, namely, environment, perception, data, communication, computation, application, action, and evaluation layer. It is important to integrate construction and FM in a loop to achieve information continuity, information credibility, life-cycle management continuity, as a way to alleviate the AECO industry’s chronic problems. The integration is proposed between SCO and cognitive FM. SCO can serve as a hardware foundation and software interface of sensing and computing to achieve awareness, communicativeness, and autonomy. Cognitive FM, in turn, will be a platform for the implementation of SCOs. With the awareness, communicativeness, and autonomy of SCOs as a backbone, the perception, learning, and action of cognitive FM system will be better achieved. Two scenarios, proactive structure assessment and life-cycle MEP system monitoring, are proposed and explained to validate the integrated framework of SCO and cognitive FM.

The global construction industry has witnessed the prolific development of radio-frequency identification (RFID), building information modeling (BIM), and most recently, linkage of the two. However, comparatively little attention has been paid to understanding the status quo and development trajectory of such RFID-enabled BIM systems. In view of the proliferation of existing RFID, BIM, and information linkage, practitioners would benefit from guidelines for choosing systems so that their construction engineering and management (CEM) needs can be better met. Accordingly, the study described in this paper has two interconnected research aims: (1) to identify current patterns and development trends in RFID-enabled BIM systems; and (2) to develop guidelines for choosing appropriate solutions for different CEM scenarios. A review of 42 actual cases published in scholarly papers reveals that RFID, used to identify objects and improve real-time information visibility and traceability, is now increasingly linked to BIM as a central information platform. This study provides practitioners with five-step guidelines for linking RFID to BIM for various CEM needs. It also provides researchers with a point of departure for further exploration of approaches to enhancing the value of RFID, BIM, and the integration of one with the other.

Building information modeling (BIM) plays an important role in furthering value-creation of construction projects by advocating the inter-firm cooperation. When implementing BIM, however, individual firms inherently safeguard their self-interests regardless of the fact that inter-firm cooperation might reap joint BIM benefits for a project overall, which epitomizes a typical problem of moral hazards in project-based organizations. This paper develops an outcome-linked benefit sharing model that considers sharing joint BIM benefits among stakeholders including designers, contractors, and clients for tracking moral hazards therein. By modeling stakeholders' behaviors as evolutionary games within a principal–agent formalism, it has been deducted that (1) designers/contractors could be incentivized to cooperate had each stakeholder received a share higher than the quotient of BIM costs over value-creation in the design/construction phase; and (2) how joint BIM benefits can be more than noncooperation outcomes is key for clients to support BIM implementation.

Managing complex and dynamic construction projects is challenging because it relies highly on the real-time communication and seamless coordination of numerous things and people that are sp...

Lactobacillus acidophilus NCFM, a probiotic generally regarded as safe, carries a proteinaceous surface (S) layer, composed of numerous identical subunits (surface layer protein, Slp). S-layer proteins have been confirmed to possess multiple biological properties, but their role in maintaining the intestinal epithelial barrier is not fully known. We investigated the effects of Slp on tumor necrosis factor (TNF)-α-elicited intestinal barrier dysfunction and explored the underlying molecular mechanism. TNF-α administration markedly induced intestinal epithelial injury and inflammation in Caco-2 cells. Preincubation of Caco-2 cells with Slp at concentrations ranging from 50 to 100 μg/mL for 6 h improved intestinal epithelial cell integrity and permeability, restored ZO-1 and Occludin protein expressions (P

The objective of this study was to evaluate the bactericidal effects of surface-layer protein (Slp) derived from Lactobacillus acidophilus NCFM, L. acidophilus CGMCC1.1878 in combination with nisin against Staphylococcus aureus and investigate their antibacterial mechanism. Compared with the nisin (MIC, 300 IU/mL) alone treatment, the Slps (50 μg/mL) + nisin (1/2 MIC, 150 IU/mL) treatment effectively inhibited S. aureus growth and significantly enhanced its cell membrane permeability (P

The elevation of atmospheric CO

Research and development (R&D) of smart construction systems has been constrained by the contentious relationship between system developers and potential industry users. System developers a...

The development of radio frequency identification (RFID) technologies has drawn notable attentions in recent studies in the construction industry. However, the initiatives of RFID technologies and RFID-enabled management systems are yet to be fully accepted and adopted in practice. The management systems seem caught in a labyrinth whereby technology developers complain that practitioners are notorious to embrace new technologies, while practitioners view the systems ‘disruptive’, if not useless altogether. By collecting qualitative research data from construction practitioners who are actively engaged in a RFID-enabled management platform implementation, this study explores the factors influencing these practitioners for accepting the system. An extended technology acceptance model (TAM) is proposed as a guiding framework to provide a better understanding of these practitioners’ adoption and use behaviors. Findings mesh with extended TAM indicating that ‘perceived usefulness’ and ‘perceived ease of use’ are of major influence to their attitude toward technology adoption. Moreover, the research demonstrates that the construction practitioners’ attitude are changing and heavily affected by the project managers who take the roles of system execution, or by peers who have harvested the benefits of such system. The findings of this study are not designed to be generalized but to offer a new perspective and insights to future TAM studies.

Emerging technologies like massive point cloud from laser scanning and 3D photogrammetry enabled new ways of generating ‘as-built’ building information models (BIM) for existing buildings. It is valuable but also challenging to generate semantic models from point cloud and images in automated ways. In this paper, we present a novel method called Optimization-based Model Generation (OMG) for automated semantic BIM generation. OMG starts from a semantic BIM component dataset and a target measurement such as point cloud, photographs, or floor plans. A fitness function is defined to measure the matching level between an arbitrary BIM model and the target measurement without object recognition. Combinations of digital components are then extensively generated as building models regarding semantic constraints. The fittest model that matches the target measurement best is the result of OMG. The proposed method was demonstrated in reconstructing a 3D model of a demolished building. Advantages of OMG include high-level automation, low requirement on measurement, relationship discovery for components, reusable component libraries, and scalability to new environments.

It has been widely accepted that developing and maintaining a cyber system (e.g. Building Information Modeling) representing the corresponding physical system is a promising approach to improve decision-making in construction. However, to bridge the bi-directional coordination between the virtual and the physical system is the prerequisite for the improvement, yet this is the most challenging part for researchers and practitioners. Using tower crane as a case study, the primary aim of this study is to propose a cyber-physical system by articulating its system structure, bridging technologies, and its computational applications. Particularly, a smart core is developed to integrate real-time information on physical machinery on site with their ‘cyber twins’ in virtual, which is developed as a web-based platform. A LEGO® tower crane is built and simulated in lab, showing the cyber and physical systems can be well bridged to facilitate safety management and resource utilization in construction projects.

A consistent and easily recognizable name is the primary identifier of an object in building information modeling (BIM). Existing naming conventions vary significantly and require extensive...

The new residential property price in Hong Kong has rocketed in the last decade and has ranked within the top three metropolitan cities in the world. Housing is a necessity for most people, high residential property price has its social ramification. The rocketing price seems not solely the result of the market. As such, this raised the issue of competition in this market. This study employs Concentration Ratio and Hirfindahl-Hirschman index to evaluate the market concentration of the New Private Resident Units Market in Hong Kong. Using the best information available in the public domains and applying universal thresholds, the New Private Resident Units Market in Hong Kong is considered moderately concentrated. It is noted that the big five listed developers in Hong Kong are collectively holding a dominant position of the potential supply. Moreover, the top three have comparable market shares thus suggesting no monopoly exists. It is also found that the substantial land banks held by the five big listed developers, amount to 60% of that owned by the Government. These developers will therefore retain their dominant market power in the future. Further study is recommended to examine whether the big developers have abused their market power.

Logistic and supply-chain management (LSCM) is of paramount importance to a construction project but is often problematic. Many researchers see LSCM per se as a web of decisions to be made, and attribute problems to a lack of process and information concurrence. This is exacerbated by fragmentation, discontinuity, and heterogeneity in construction LSCM. The bidirectional information flow remains unachieved in the existing sensing-based systems for construction LSCM. Without panoramically interconnecting to other smart abilities such as an automatic action-taking ability, most existing sensing-based systems are insufficient to realize their full potential in facilitating construction LSCM. Building on previous studies on smart construction objects (SCOs), this paper aims to develop an SCO-enabled system that can enhance concurrence of process and information, with a view to informing better decision making in construction LSCM. It does so by first analyzing the problems in prevailing LSCM practices...

The primary aim of this research is to define smart construction objects (SCOs), the fundamental building blocks of future construction. SCOs are construction resources (e.g., machinery, device, and materials) that are made smart by augmenting them with technologies conferring autonomy, awareness, and the ability to interact with their vicinity. This smartness can enable better decision making in construction. Understanding of SCOs, however, is still in its infancy. Informed by theories on ubiquitous computing and general smart objects, this paper first defines the panoramic and interconnected properties that differentiate SCOs from conventional construction objects. Second, representative scenarios of the use of SCOs are given to illustrate the new workflow with enhanced smartness in the future. Next, using prefabrication construction as an example, this paper further elaborates SCOs using Industry Foundation Classes Extensible Markup Language and exploring their software/hardware representations...

Prefabrication construction has been increasingly applied to the construction industry. Automation and intelligentization of construction site and construction objects has become the fore for the development of the prefabrication construction. In this study, a SCO-based tower crane system, as the core resource site on the critical path of prefabrication construction, is proposed to make the cranes more intelligent and efficient. A set of smart units are applied to the tower cranes and prefabricated components to make them into Smart Construction Objects (SCOs), enabling the functions of awareness, communicativeness and autonomy. The smart tower crane could “talk” with prefabrication components through sensors and real-time wireless connections. A system operation flow is developed for fetching and placing target components. The SCO-based tower crane system can provide the operation instruments, real-time traceability of the components, and necessary warning. The system is being tested in a pilot project, which is delivered through BIM and prefabrication construction. It is envisaged that the SCO-based tower crane system could significantly improve the safety performance and operation efficiency of the tower crane operations in prefabrication construction.

The building information modeling (BIM) has been under aggressive promotion by governments throughout the world. By contrast, the Architecture, Engineering, and Construction (AEC) industry shows reluctance to adopt BIM in its projects. Two questions are immediate: why the market hesitates with BIM adoption; and whether the governmental compulsory BIM implementation is regarded as reasonable. Previous literature is in-depth but is distant from the market, which have failed in analyzing the basic reasons lying behind. This study aims to provide an alternative explanation. Based on the assumption that any market activity is to maximize economic profits, this study concluded that (1) since BIM adoption involves opportunity costs, stakeholders would choose to adopt BIM at the market-determined time; (2) due to the social costs/benefits of using BIM, the market-determined timing of BIM adoption tends to be delayed, the governments’ enforcing BIM hence is reasonable; and (3) the compulsory requirements on clarifications of the responsibilities and the corresponding benefits among AEC disciplines reinforces the importance of governments in promoting BIM implementation.

Competition is a key to maintaining a healthy market without price distortion. With the occurrence of increasing anti-competition conducts and climbing project price in the building maintenance business in Hong Kong, it is of importance to examine the appropriate degree of competition (DOC) in this booming market. Market share concentration, entry barrier and other factors have been proposed by previous studies to examine the market competition individually. However, method that takes all factors into consideration for measuring the competition degree of the building maintenance market has not been established. This study aims to provide a conceptual model, by taking these factors on board to measure the DOC of the building maintenance market in Hong Kong. The model could be used to guide data collection, data processing and the calculation of the DOC. Measurement outcomes from this model may provide a basis for assisting the enforcement of the Competition Ordinance enacted from 2012 as well as alarming the enterprises with malpractices in the market.

The effect of the introduction of nano-fillers into polyethylene on space charge accumulation is usually studied in electric fields reaching 100kV/mm using thin 100 μm samples, which is much thinner than the insulation in actual HVDC cables. Our previous work showed that space charge distributions in LDPE and its nanocomposites have different thickness dependences at isothermal temperature (20°C and 60°C). This was explained using the bipolar model and trapping potential model. However, in actual cables the temperature is not isothermal, but has a gradient, so we have investigated the space charge distribution in unfilled XLPE and its SiO2 nanocomposites under different temperature gradients at 50kV/mm. It is found that the unfilled XLPE space charge distributions definitely have thickness dependence under a temperature gradient. The XLPE/SiO2 nanocomposites also show strong thickness dependence: the thin samples accumulate large heterocharge densities, but the thicker the sample is, the less the heterocharge accumulates and even under a temperature gradient the 0.5mm nanocomposites still suppress most of the heterocharge.

The detection of Ultra high frequency (UHF) Electromagnetic wave(EM) induced by partial discharge (PD) has been applied in power transformer to find insulation defects due to such features as interference-free and abundant discharge information. However, the propagation mechanism of UHF EM in power transformer has not been detailed investigated, and there are few effective results to instruct the field detection of UHF PD and fault diagnosis. In this paper, a simulation model based on Finite-difference time-domain (FDTD) was proposed, and the propagation characteristics of UHF EM from three PD locations (interturn, oil clearance and outside winding) were investigated. The magnitude, frequency and attenuation of the UHF EM were compared after it passes through the winding. In this model, Gaussian pulse with different amplitude and width is used for equivalent PD current. Results show that the UHF EM from different positions will be damped oscillation at some characteristic frequency when it passes through the winding. The UHF PD signal from interturn has more oscillation duration than other locations. Otherwise, the UHF PD oil clearance and outside windings contain more spectrum information. A simple transfer function between the amplitude of UHF EM and that of PD current was got. It indicates that the shape and spectrum of UHF EM are independent with the amplitude of PD current. The size of winding and oil clearance is the main factor to affect the frequency of UHF signals.