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Literature defines two main streams in project management: mechanistic and organic. Mechanistic reflects the traditional waterfall approach and organic reflects a more adaptive approach. The organic approach became known by the awareness of dynamic project environment and changing requirements. The organic approach is characterized by flexibility. Accordingly, scholars and practitioners tried to define flexibility and find ways to make project management more flexible. However, scientific literature about practitioners’ perspectives on making project management flexible is lacking. Therefore, this paper explores practitioners’ perspectives on project management flexibility by the use of Q-methodology. The scope of the paper was narrowed down to the front-end phase of infrastructure projects. Two types of organizations were targeted: client and consultancy organizations. Data were gathered from 43 respondents from six organizations (three client and three consultancy organizations) in The Netherlands. The results of the study reveal three distinct perspectives on flexibility for both organization types (client and consultant): flexibility by trust, flexibility by scope management, and flexibility by proactive management. These perspectives partly support defined flexibility categories in literature. Further research could focus on exploring the perspectives in different project phases, operationalizing the perspectives in practice, and team composition taking into account these perspectives. [ABSTRACT FROM AUTHOR]

This paper presents a magnetic safety evaluation of the static magnetic field produced by magnetic floors with permanent magnet properties utilized in the construction industry. The magnetic floors analyzed in this paper are composed by a concentration of 85% of isotropic strontium (Sr) ferrite powder mixed with chlorinated polyethylene. The magnetic floors are magnetized and tested in the laboratory to measure the magnetic field levels in different regions of the magnetic floors and magnetic subfloors. Finite-element (FE) simulations are carried out to compute the magnetic field produced by magnetic floors. The numerical results and laboratory tests are compared and analyzed. Values of the magnetic field between 2 and 50 mT are computed and measured in different regions of magnetic floors. Finally, the static magnetic field levels obtained in the magnetic floors are compared with the permitted magnetic field values for different electronic devices, pacemakers, and other common objects utilized by persons in buildings. The results obtained in this paper show that magnetic floors are safe, and they can be employed in buildings without putting in risk electronic devices or persons with pacemakers. [ABSTRACT FROM AUTHOR]

Supplier development (SD) has become an emerging supply chain management practice for firms focusing on their core strategic advantages by outsourcing a significant portion of production or construction activities. Various incentive mechanisms are available for suppliers to improve their capabilities to meet owners’ expectations. However, a comparative analysis is needed to understand how successful they are. This paper investigates the incentive mechanisms for SD in a construction supply chain that consists of one owner and one supplier. Considering the owner's dominant position in the negotiation of a supply contract, a principal–agent model with the objective of optimizing the owner's profit and a Stackelberg game model designed to optimize the profits of both the owner and supplier are proposed and analyzed. Two commonly used incentive methods, including purchase price incentive and cost sharing, are analyzed and compared. The analysis and comparison are illustrated by a numerical example. The primary contribution of this paper is the analysis of the impact of incentive methods on quality improvement for the supplier and a sensitivity analysis of the supplier's internal and external factors, such as purchase quantity, market demand, and manufacturing cost structures, which are useful managerial insights for SD practices in mega construction projects. [ABSTRACT FROM AUTHOR]

In relation to automated 3D concrete construction printing, a structure design of a suitable robot manipulator is presented as well as analytical solutions of related kinematics. The proposed structure has a higher number of degrees of freedom which can significantly increase the dexterity of a robot end-effector carrying a printing head. It should perform a continual motion along complicated large-scale printing trajectories. The related robot kinematics is derived by a novel representation of working layers in the complex plane using exponential functions. It leads to an explicit derivation of kinematic equations. The theoretical results are presented by examples of motion trajectories with typical configurations of the proposed structure. Note to Practitioners—This paper deals with a design of suitable robot structures for 3D concrete printing. Such concept is determined for on-site printing of residential houses. This area is developing a lot, but without a systematic design of energy-efficient, space-fitting robotic arms. A suitable structure is proposed, including a kinematic description to determine joint coordinates necessary for robot motion control. To ensure continuous energy-balanced motion during a large-scale printing, the redundant links in the structure are also used. Next research tasks focus on trajectory optimisation in complex print profiles. [ABSTRACT FROM AUTHOR]

Fatal accidents caused by electric shock have been occurring since electricity was first introduced. Overall, the number of fatal accidents is decreasing. However, the decrease in the number of fatalities has slowed in recent years. A statistical study is needed to reconsider the preventive measures against these accidents. In this paper, the trend of fatalities by accident type and industry in Japan is studied statistically. These results show that the electric fatality rates differ by industry. The fatalities in the construction and the electrical-construction industries make up approximately 60% of the total fatalities. In addition, the accident type is most frequently contact with electrical lines by either the human body or a tool. In these industries, the elimination of fatal accidents from shocks is an important subject. These results will be helpful in preventing fatal accidents by electric shock. [ABSTRACT FROM PUBLISHER]

Augmented reality (AR) allows for an on-site presentation of information that is registered to the physical environment. Applications from civil engineering, which require users to process complex information, are among those which can benefit particularly highly from such a presentation. In this paper, we will describe how to use AR to support monitoring and documentation of construction site progress. For these tasks, the responsible staff usually requires fast and comprehensible access to progress information to enable comparison to the as-built status as well as to as-planned data. Instead of tediously searching and mapping related information to the actual construction site environment, our AR system allows for the access of information right where it is needed. This is achieved by superimposing progress as well as as-planned information onto the user's view of the physical environment. For this purpose, we present an approach that uses aerial 3-D reconstruction to automatically capture progress information and a mobile AR client for on-site visualization. Within this paper, we will describe in greater detail how to capture 3-D, how to register the AR system within the physical outdoor environment, how to visualize progress information in a comprehensible way in an AR overlay, and how to interact with this kind of information. By implementing such an AR system, we are able to provide an overview about the possibilities and future applications of AR in the construction industry. [ABSTRACT FROM PUBLISHER]

In some of recent advances in automation of construction equipment, much research has been conducted on the control of hydraulic excavators in both industry and academia for the benefit of safety and efficiency. However, most relevant works have employed model-based control approaches that require a mathematical representation of the target plant. For hydraulic excavators, obtaining a useful dynamic model for control can be challenging due to the nonlinearity of the hydraulic servo system. With this in mind, this paper investigates the feasibility of an online learning control framework based on echo-state networks (ESNs) to the position control of hydraulic excavators. While ESNs are a class of recurrent neural networks, the training of ESNs corresponds to solving a linear regression problem, thus making it suitable for online implementation. By exploiting the dynamic properties of ESNs, the deployed control framework uses the input and output signals of the plant to learn an inverse model, which is then used to simultaneously generate control inputs to track the desired trajectory. Experiments conducted on a 21-ton class hydraulic excavator show the promising results in that accurate tracking is achieved even in the absence of a dynamic model. [ABSTRACT FROM AUTHOR]

The continuation and improvement of preventive measures and safety training following electrical accidents are important in reducing the number of accidents in the workplace. A consideration of these preventive measures based on case studies of electrical accidents is required. Consideration may not be sufficient in Japan and other countries, because many electrical accidents involve electric shocks. Thus, continuation and improvement of electrical safety measures are needed. Several research papers on electrical accidents in the workplace have been published; however, a detailed consideration and analysis of case studies are also important, because safety culture and electrical installation differ by country. The use of less than 35-V products and equipment may be needed for thorough prevention of fatal electrical accidents. There are some differences in voltage level by country, which may cause a problem in ultimately reducing the number of accidents. In this study, 349 cases were considered. An assessment of electrocutions has never been performed in Japan; therefore, this paper will summarize the circumstances of electrocutions in Japan based on industry statics. It is the author's expectation that the results will assist in developing possible engineering solutions to reduce electrical accidents. [ABSTRACT FROM AUTHOR]

This paper presents a model predictive control (MPC) strategy for a hydraulic multichamber actuator. The actuator of interest is a hydraulic cylinder with four cylinder chambers connected to a common pressure rail through a set of hydraulic valves. The control challenge is to achieve accurate force control with preserved energy efficiency at all times. MPC is here used to overcome the difficulties in mode switching, being a multivariate control problem that involves fast pressure dynamics. For this, a simplified internal model is conceived while the energy efficiency aspect is managed by a separate controller, referred to as the force index controller. Simulations reveal how different controller variations affect the tradeoff between energy efficiency and force tracking performance. Due to its relevance to energy efficiency, the study highlights how the switching losses stand in relation to throttle losses. [ABSTRACT FROM AUTHOR]

Large construction and infrastructure projects are a billion-dollar business, but few studies have addressed the integrated operations in this unique domain of the construction supply chain (CSC). The comparison between the CSC and a conventional supply chain enables us to examine its framework and establish a quantitative optimization model for the CSC. To introduce the integrated operations concept into the CSC, many uncertainties need to be first dealt with, for which a multiobjective uncertain optimization model is developed. As the optimization of the owner and fabricator's costs and the service level are the main objectives, a hybrid genetic algorithm with fuzzy-random method is developed to solve the optimization model. An integrated multiobjective purchasing and production planning model is then constructed and applied to a hydropower construction project in Southwest China. The results illustrate that efficient integrated operations are critical for the CSC performance. The optimization results also indicate that considering of uncertain rush orders and delay times can be vital for optimum CSC performance. With this proposed method, construction managers can quickly respond to changing uncertain demand. This paper has highlighted that project managers need to collaborate with other stakeholders to ensure optimal CSC performance. [ABSTRACT FROM AUTHOR]

Mega-engineering projects in the construction industry are generally carried out by public–private partnership models with the participation of different stakeholders. This paper aims to identify the effect of stakeholder-associated risks on the success of mega-engineering projects. Therefore, the risks were determined and then validated by focus discussions. Afterwards, an illustrative case study was presented to better understand the effects. Finally, a fuzzy analytical hierarchy process method was used to prioritize the identified risks. The prominent risks were found to include “improper partner selection,” “inadequate relationships with employer,” and “incompetent contractor selection.” Engineering managers need to work in close coordination with all members of the project. To better manage projects, engineering managers are expected to be familiar with the concepts of project risk management, because effective project risk management has a direct and positive effect on project management performance. Professionals in the field of engineering management can benefit greatly from the findings of this study by using it as a baseline for coordinating the relationships in multistakeholder organizational structures and analyzing stakeholder-associated risks throughout their projects. [ABSTRACT FROM AUTHOR]

The aim of this paper is to simulate the performances of a ground fault circuit-breaker (GFCB) relay with new low-nickel-content alloys. Indeed, in the construction industry, the materials become more expensive as their nickel content increases. Moreover, the demand for nickel is particularly sensitive to the economic conjuncture. Therefore, an original electromagnetic relay model has been developed and validated in different working conditions (current amplitude, frequency, and temperature). A dedicated magnetic characterization of materials is needed, using basically a usual and industrial GFCB relay for reference and design data in modeling. First, the magnetic model of the relay is built and checked against experimental data. The simulation may predict the tripping current threshold of the relay. On the other hand, new low-nickel-content alloys for relay parts are studied in this framework, thanks to the developed model. The effects of temperature on the magnetic properties of the candidate materials and the electrical performances of the virtual relays are presented. The results, analysis, and conclusions are given. Finally, a first attempt to predict the economic gain obtained with a change of material is made. [ABSTRACT FROM AUTHOR]

This paper examines the torque ripple and cogging-torque variation in permanent-magnet synchronous motors (PMSMs). The effect of slot number and magnet skewing on electromagnetic motor torque, has been analyzed in different 20-pole, three-phase, PMSM configurations having the same envelop dimensions and output requirements. Finite-element technique is used for machine characteristics computation. Maxwell-stress tensor is used to find torque. Finite-element analysis results show that: 1) motors with fractional-slot winding have lower torque ripple but show a reduction of the average torque and 2) in step-skew magnet motors, torque-ripple reduction is significant only for a certain step number and magnet-skew angle. [ABSTRACT FROM PUBLISHER]

In wireless sensor networks, it is already noted that nearby sensor nodes monitoring an environmental feature typically register similar values. This kind of data redundancy due to the spatial correlation between sensor observations inspires the research of in-network data aggregation. In this paper, an \alpha-local spatial clustering algorithm for sensor networks is proposed. By measuring the spatial correlation between data sampled by different sensors, the algorithm constructs a dominating set as the sensor network backbone used to realize the data aggregation based on the information description/summarization performance of the dominators. In order to evaluate the performance of the algorithm a pattern recognition scenario over environmental data is presented. The evaluation shows that the resulting network achieved by our algorithm can provide environmental information at higher accuracy compared to other algorithms. [ABSTRACT FROM PUBLISHER]

This paper tackles the collision-avoidance problem in air traffic management. The problem consists of deciding the best strategy for new aircraft configurations (velocity and altitude changes) such that all conflicts in the airspace, i.e., the loss of the minimum safety distance that has to be kept between two aircraft, are avoided. A mixed 0–1 linear optimization model based on geometric transformations for collision avoidance between an arbitrary number of aircraft in the airspace is developed. Knowing the initial coordinates, angle direction, and level flight, the new configuration for each aircraft is established by minimizing several objective functions, e.g., velocity variation and total number of changes (velocity and altitude), and forcing to return to the original flight configuration when no aircraft are in conflict. Due to the small computational time for the execution, the new configuration approach can be used in real time by using optimization software. [ABSTRACT FROM PUBLISHER]

The discrete pulse transform (DPT) is a decomposition of an observed signal into a sum of pulses, i.e., signals that are constant on a connected set and zero elsewhere. Originally developed for 1-D signal processing, the DPT has recently been generalized to more dimensions. Applications in image processing are currently being investigated. The time required to compute the DPT as originally defined via the successive application of LULU operators (members of a class of minimax filters studied by Rohwer) has been a severe drawback to its applicability. This paper introduces a fast method for obtaining such a decomposition, called the Roadmaker's algorithm because it involves filling pits and razing bumps. It acts selectively only on those features actually present in the signal, flattening them in order of increasing size by subtracing an appropriate positive or negative pulse, which is then appended to the decomposition. The implementation described here covers 1-D signal as well as two and 3-D image processing in a single framework. This is achieved by considering the signal or image as a function defined on a graph, with the geometry specified by the edges of the graph. Whenever a feature is flattened, nodes in the graph are merged, until eventually only one node remains. At that stage, a new set of edges for the same nodes as the graph, forming a tree structure, defines the obtained decomposition. The Roadmaker's algorithm is shown to be equivalent to the DPT in the sense of obtaining the same decomposition. However, its simpler operators are not in general equivalent to the LULU operators in situations where those operators are not applied successively. A by-product of the Roadmaker's algorithm is that it yields a proof of the so-called Highlight Conjecture, stated as an open problem in 2006. We pay particular attention to algorithmic details and complexity, including a demonstration that in the 1-D case, and also in the case of a complete graph, the Roadmaker's algorithm has optimal complexity: it runs in time \cal O(m), where m is the number of arcs in the graph. [ABSTRACT FROM AUTHOR]

An increasing number of decision support systems based on domain knowledge are adopted to diagnose medical conditions such as diabetes and heart disease. It is widely pointed that the classical ontologies cannot sufficiently handle imprecise and vague knowledge for some real world applications, but fuzzy ontology can effectively resolve data and knowledge problems with uncertainty. This paper presents a novel fuzzy expert system for diabetes decision support application. A five-layer fuzzy ontology, including a fuzzy knowledge layer, fuzzy group relation layer, fuzzy group domain layer, fuzzy personal relation layer, and fuzzy personal domain layer, is developed in the fuzzy expert system to describe knowledge with uncertainty. By applying the novel fuzzy ontology to the diabetes domain, the structure of the fuzzy diabetes ontology (FDO) is defined to model the diabetes knowledge. Additionally, a semantic decision support agent (SDSA), including a knowledge construction mechanism, fuzzy ontology generating mechanism, and semantic fuzzy decision making mechanism, is also developed. The knowledge construction mechanism constructs the fuzzy concepts and relations based on the structure of the FDO. The instances of the FDO are generated by the fuzzy ontology generating mechanism. Finally, based on the FDO and the fuzzy ontology, the semantic fuzzy decision making mechanism simulates the semantic description of medical staff for diabetes-related application. Importantly, the proposed fuzzy expert system can work effectively for diabetes decision support application. [ABSTRACT FROM AUTHOR]

Most model-based approaches to fault diagnosis of discrete-event systems (DESs) require a complete and accurate model of the system to be diagnosed. However, the discrete-event model may have arisen from abstraction and simplification of a continuous time system or through model building from input–output data. As such, it may not capture the dynamic behavior of the system completely. In this paper, we address the problem of diagnosing faults, given an incomplete model of the discrete-event system. When the model is incomplete, discrepancies will arise between the actual output and the output predicted by the model. We introduce learning into the diagnoser construction by forming hypotheses that explain these discrepancies. We view the process of generating and evaluating hypotheses about the model of the system as an instance of the set-cover problem, which we formalize using parsimonious covering theory. We describe in detail the construction of the learning diagnoser, which not only performs fault diagnosis but also attempts to learn the missing model information. If the model is complete, the learning diagnoser reduces to the standard state-based diagnoser. Examples are provided to illustrate how learning and diagnosis can be simultaneously achieved through the learning diagnoser. [ABSTRACT FROM AUTHOR]

This paper proposes a new rolled fingerprint construction approach incorporating a state-of-the-art nonrigid image registration method based upon a Markov random field (MRF) energy model. The proposed method finds dense correspondences between images from a rolled fingerprint sequence and warps the entire fingerprint area to synthesize a rolled fingerprint. This method can generate conceptually more accurate rolled fingerprints by preserving the geometric properties of the finger surface as opposed to ink-based rolled impressions and other existing rolled fingerprint construction methods. To verify the accuracy of the proposed method, various comparative experiments were designed to reveal differences among the rolled construction methods. The results show that the proposed method is significantly superior in various aspects compared to previous approaches. [ABSTRACT FROM AUTHOR]

The Peano-Gosper space-filling curve provides an excellent framework for designing planar antenna array distributions with modular architectures and suppressed sidelobes over a relatively wide bandwidth. The curve consists of a self-avoiding path that intersects a triangular lattice and its construction is based on the iterative application of a generating curve. There exist a number of other recently discovered curves, coined generalized Gosper curves, that possess properties similar to those of the Peano-Gosper curve but are based on larger and more complex generating curves. In this paper these generalized curves will be examined as the framework for antenna array layouts. It will be shown that arrays based on these curves have a number of excellent characteristics while offering modular array configurations and sizes that are not inherent to Peano-Gosper arrays. Moreover, when combined with a simple recursive-perturbation technique, the element distributions of these arrays can be efficiently adjusted to generate designs with bandwidths that far exceed that of standard periodic- and triangular-lattice arrays. The efficacy of this technique will be demonstrated through design examples, including one that has more than a 10:1 bandwidth. Full-wave simulations of a wideband patch array will also be used to investigate the effects of mutual coupling on these array distributions. [ABSTRACT FROM AUTHOR]

This paper proposes an improved subspace-based optimization method (SOM) by using a new construction method for the ambiguous part of the induced current. The new current construction method reduces not only the computational complexity of the current construction in every iteration of the optimization but also the computational complexity of the singular-value decomposition of the mapping from the induced current to scattered fields. Thus, the improved SOM is able to deal with the 3-D inverse-scattering problems. Numerical tests validate the algorithm. [ABSTRACT FROM AUTHOR]

This paper presents the forward kinematics of the casing oscillator, which is a heavy construction machine. This machine has a four-degrees-of-freedom (DoF) parallel mechanism with one redundancy. By using the geometric approach, the forward position kinematics for the casing oscillator is derived as a fourth-order polynomial equation in square form of one output variable [ABSTRACT FROM PUBLISHER]

The Fourth Industrial Revolution (Industry 4.0) is reshaping the construction industry and bringing it into an intelligent construction era. Emerging technologies, such as the Building Information Modelling, Internet of Things, big data, cloud computing, and artificial intelligence, have penetrated into all stages of the building life cycle and play a significant role. However, the major issue of intelligent construction is integrating multiple technologies to create more potential opportunities rather than their fragmented application. Considering the various special characteristics of the construction industry and the high heterogeneity of these technologies, their integration in the construction industry is challenging and requires in-depth investigations. This paper summarizes the Industry 4.0-related technologies involved in the construction industry based on an analysis of the characteristics of the industry. Further, this study presents a framework of a cyber-physical system to integrate these technologies and improve the overall capabilities of construction organization and management. A case study of the Xiong'an citizen service center is introduced to verify the technological feasibility and preliminary implementation effect of the proposed framework. As forward-looking research, the significance of this paper may also to inspire more efforts in this field.

The problem addressed in this paper is the challenge of automated construction of knowledge discovery workflows, given the types of inputs and the required outputs of the knowledge discovery process. Our methodology consists of two main ingredients. The first one is defining a formal conceptualization of knowledge types and data mining algorithms by means of knowledge discovery ontology. The second one is workflow composition formalized as a planning task using the ontology of domain and task descriptions. Two versions of a forward chaining planning algorithm were developed. The baseline version demonstrates suitability of the knowledge discovery ontology for planning and uses Planning Domain Definition Language (PDDL) descriptions of algorithms; to this end, a procedure for converting data mining algorithm descriptions into PDDL was developed. The second directly queries the ontology using a reasoner. The proposed approach was tested in two use cases, one from scientific discovery in genomics and another from advanced engineering. The results show the feasibility of automated workflow construction achieved by tight integration of planning and ontological reasoning. [ABSTRACT FROM AUTHOR]

Most of the existing methods to solve the problem of association rules mining (ARM) rely on special data structures to project the database (either totally or partially) in the primary memory. Traditionally, these data structures reside in the main memory and rely on the existing paging mechanism of the virtual memory manager (VMM) to handle the storage problem when they go out of the primary memory. Typically, VMM stores the overloaded data into the secondary memory based on some preassumed memory usage criteria. However, this direct and unplanned use of virtual memory results in an unpredictable behavior or thrashing, as depicted by some of the works described in the literature. This problem is tackled in this paper by presenting an ARM model capable of mining a transactional database, regardless of its size and without relying on the underlying VMM; the proposed approach could use only a bounded portion of the primary memory and this gives the opportunity to assign other parts of the main memory to other tasks with different priority. In other words, we propose a specialized memory management system which caters to the needs of the ARM model in such a way that the proposed data structure is constructed in the available allocated primary memory first. If at any point the structure grows out of the allocated memory quota, it is forced to be partially saved on secondary memory. The secondary memory version of the structure is accessed in a block-by-block basis so that both the spatial and temporal localities of the I/O access are optimized. Thus, the proposed framework takes control of the virtual memory access and hence manages the required virtual memory in an optimal way to the best benefit of the mining process to be served. Several clever data structures are used to facilitate these optimizations. Our method has the additional advantage that other tasks of different priorities may run concurrently with the main mining task with as little interference as possible because we do not rely on the default paging mechanism of the VMM. The reported test results demonstrate the applicability and effectiveness of the proposed approach. [ABSTRACT FROM AUTHOR]

This paper presents the development of an energy-conditioning system for a proton exchange membrane (PEM) type fuel cell (FC). The developed system provides 230 V ac rms at 50 Hz, with a nominal output power of 1 kVA, and is able to handle sporadic high-power demands up to 5 kVA. An auxiliary power unit (APU), using a bank of supercapacitors as energy-storing device, provides this extra power during a certain amount of time. The output current ripple and step response constraints of the FC unit are considered in the design. A frequency-decoupling scheme is used, in which the FC provides only the low-frequency requirements, while the fast/high-frequency demands are supplied by the APU. A detailed description is given for its different constructive modules, their control design, and implementation. [ABSTRACT FROM PUBLISHER]

In the Russian State Research Center, Troitsk Institute of Innovation and Fusion Research, the first two power-amplifier cascades of the MOL stand are put into operation. This paper presents the description of the stand stages and the results of experiments on the current amplification. In the experiment, under the MOL's charging current of 20 kA, the second-stage output current of 1.6 MA was obtained. [ABSTRACT FROM AUTHOR]

This paper presents a multiagent system to manage and monitor the surveillance routes of the security personnel in the construction sector. Several concepts, derived from the Artificial Intelligence, have been taken into account for the system design, obtaining context information in order to automatically monitor the surveillance routes in execution time. The system is composed of intelligent agents with reasoning and planning capabilities, as well as of a set of technologies allowing users to interact with the system and the environment in a natural, unobstructive and easy way. [ABSTRACT FROM PUBLISHER]