RFID indoor location identification for construction projects

This paper presents a low cost indoor location identification and material tracking methodology for construction projects using Ultra High Frequency (UHF) passive Radio Frequency Identification (RFID) technology. Onsite location aware information is an emerging area that focuses on automating delivery of spatial information pertinent to location of materials, workforce, and equipment. This spatial information can be used to derive knowledge about construction project status. A two-step algorithm is presented to automate the process of location estimation and material tracking in near-real-time. In this methodology, a number of passive RFID tags are distributed onsite where work is progressing, and a mobile RFID reader is carried by a worker onsite. Each passive RFID tag is deployed as a reference point with a known location (landmark) within a predefined zone. Reference tags of known locations are used to determine the location of the worker and eventually locate and track surrounding materials. The methodology uses Received Signal Strength Indicator (RSSI) for signal measurements. Two localization methods (triangulation and proximity) were used to identify the location of the worker. Testing this methodology was carried out on an actual construction jobsite, where five test beds were setup at different locations and within different construction time spans. In addition, one test bed was set up in a lab environment. The results presented in this study demonstrate the potential for a low-cost method for location estimation and material tracking of indoor construction. The results show a mean error of 1.0 m and 1.9 m for user location identification and material tracking using the triangulation method, respectively. The results also show a mean error of 1.9 m and 2.6 m for location identification of the worker and for material tracking using the proximity method, respectively. The proposed methodology detects the zones of worker and material location with 100% accuracy.     

A fast and precise methodology of creep master curve construction for geosynthetics based on stepped isothermal method (SIM)

The variability of the virtual time of stepped isothermal method (SIM) was observed during the creep master curves construction of a new high-performance geosynthetics material, which led to the significant errors in predicting the long-term creep. After analyzing the process of construction, the difference in selecting the beginning and end segments is the reason causing the errors. Therefore, a set of computer-based routine was programmed to eliminate the errors. Based on the amount of data of SIM and conventional creep tests, the virtual time of each corresponding step, the curves of scaled creep data, and the comparison between these two creep data were obtained in the present study by the routine. They were used to study the influence of different beginning segments and end segments on the master creep curve. Overall, The 5% of elevated temperature step and 50% of the previous step is suggested to regard as the beginning segment and end segment respectively to obtain the more well-founded virtual time and more accurate creep curve. This study not only provides a reference for research focusing on accelerated creep tests but proposed a fast and accurate methodology to construct the creep master of SIM tests.     

Dynamic analysis of a bridge repaired by CFRP: Experimental and numerical modelling

A significant number of existing reinforced-concrete bridges all over the world require maintenance and repair. Hence, the need for a rapid evaluation procedure for the diagnosis of existing bridges. This paper presents the application of a dynamic analysis methodology for structural evaluation of reinforced-concrete bridges. The methodology is based on the application of ambient vibrations non-destructive testing method and the identification of the structure total response using finite element method. A case study of a three span reinforced concrete bridge in a strong seismic activity area in the north of Algeria is analysed. The ambient vibration testing was carried out on the bridge, before and after its repair by the application of carbon fibre composites. The tests were conducted using an acquisition system made up of four accelerometers with three components placed at specific locations on the bridge. The finite element model gave comparable results to the experimental ambient vibrations tests. The modal parameters of the bridge before and after repair were identified by this in situ testing. The application of composite material to strengthen the structure increases the transverse rigidity of the structure and thus its modal frequency.     

Decision support for tower crane selection with building information models and genetic algorithms

Tower cranes are major construction equipment that is highly demanded in construction projects. The planning process for tower cranes utilization starts in early stages of the construction projects. Poor selection could incur extra costs on the construction projects or cause delays in project duration. The planning procedures for tower cranes include selection, allocation and operation. This paper presents a framework for the selection of tower cranes types and locations at construction sites. The framework considers three main models: 1) decision making model to select the tower crane type, 2) optimization model for the selection of the ideal number and location of tower cranes, and 3) 4D simulation model to simulate tower crane operations. Several clash detection scenarios are presented to assure the safety operation of the tower crane group. A case study is shown herein to demonstrate the capabilities of the developed framework.     

盾构管片排版计算方法的研究

管片的排版是盾构法隧道施工中的重要研究课题。施工人员通过选择适当的管片排版方案,来实现盾构隧道的实际轴线对于设计轴线的拟合。本文基于盾构管片的几何特征,提出了对管片建立坐标系来描述管片信息的方法。利用坐标系变换的理论,并根据施工中管片的拼装点位参数,对管片的排版过程进行分析。进而推导出了管片排版计算方法。利用MATLAB模拟管片的排版计算过程,验证了方法的可行性。本文实现了对管片的排版计算,对隧道施工中管片的拼装起到指导作用。     

A new approach for automation of location-based earthwork scheduling in road construction projects

Accurate information of working locations is vital for efficient resource planning, safety of the construction site and monitoring the weekly progress of earthworks, which is missing in the existing linear scheduling methods. Construction managers have to depend on the subjective decisions for resources allocation and progress monitoring from location aspects. This has caused uncertainties in planning and scheduling, and consequently delays and cost overruns of projects. In this context, a prototype computer-based model was developed using the theory of the location-based planning. An arithmetic algorithm was designed by incorporating road design data, sectional quantities, variable productivity rates and haulage distance. This paper focuses on the improvement and demonstration of the model functions through a case study experiment, which include the automatic generation of location-based earthwork schedules and the optimisation of the weekly resource allocation when and where necessary from the location aspects, considering different options such as construction sequences of the cut/fill sections, site access points and the equipment sets with known productivity rates. The study concluded that the model is a decision supporting tool that assists in the resources planning, identifying time–space congestion, monitoring the activities progress on a weekly basis from the location aspects, and reducing the gap when communicating the scheduling information amongst the construction site teams.     

An object recognition, tracking, and contextual reasoning-based video interpretation method for rapid productivity analysis of construction operations

Measuring the process of construction operations for productivity improvement remains a difficult task for most construction companies due to the manual effort required in most activity measurement methods. This paper proposed and described the elements, processes, and algorithms that comprise a computational and intelligent construction video interpretation method. A number of vision-based construction object recognition and tracking methods were evaluated to provide guidance for algorithm selection. A prototype system was developed to integrate the proposed video analysis processes and selected computer vision algorithms. Videos of construction operations were analyzed to validate the proposed method. Comparing to the traditional manual construction video analysis method, the proposed method provided a semi-automated video interpretation method. The new method enabled the interpretation of these videos into productivity information, such as working processes, cycle times, and delays, with an accuracy that was comparable to manual analysis, without the limitations of on-site human observation.     

Application of neural networks for detecting erroneous tax reports from construction companies

In this study we develop an automatic detection model for discovering erroneous tax reports. The model uses a variety of neural network applications inclusive of the Multi-Layer Perceptrons (MLPs), Learning Vector Quantization (LVQ), decision tree, and Hyper-Rectangular Composite Neural Network (HRCNN) methods. Detailed taxation information from construction companies registered in the northern Taiwan region is sampled, giving a total of 5769 tax reports from 3172 construction companies which make up 35.98% of the top-three-class construction companies. The results confirm that the model yields a better recognition rate for distinguishing erroneous tax reports from the others. The automatic model is thus proven feasible for detecting erroneous tax reports. In addition, we note that the HRCNN yields a correction rate of 78% and, furthermore, generates 248 valuable rules, providing construction practitioners with criteria for preventing the submission of erroneous tax reports.     

Assessing multiple criteria for the optimal location of a construction and demolition waste management facility

Construction industry is the most significant fields on a global scale, with respect to its economic, technological, and environmental impact. Its rapid growth over the last decades has resulted in an enormous increase of the produced construction and demolition waste, thus provoking a considerable burden on the environment. The proposed methodological framework is aiming towards optimal location of units of alternative construction and demolition waste management and it is following the path of multicriteria analysis. For the problem under study, ELECTRE III technique is adopted. The decision process presented requires the adoption of a number of logical steps mainly, clarification of the decision criteria for selecting the optimal location (economical, environmental and social), the definition of their relative significance and data assembly. The approach allows a robust parameter analysis in order to evaluate and compare in detail all available alternatives. On top of that, sensitivity analysis is also available, since parameter values in real life applications originate from estimations which are sometimes more or less reliable. This paper presents an effort to interlace local acceptance, financial viability and level of environmental quality which represents a vital issue for the particular waste stream’s management efficiency. The methodology is implemented and demonstrated for the case of the Region of Central Macedonia, Greece and can be employed either by private investors or public authorities in other areas internationally.     

Problems influencing craftsmen''s productivity in Nigeria

The activity sampling technique was used on seven construction sites in Nigeria to determine how the working day was being utilised by craftsmen in bricklaying, joinery and steel fixing trades. Actual working time was observed to be 51% of the working day for bricklayers, 44% for joiners and 56% for steel fixers. The rest of the working day was spent on nonproductive activities. The problems causing nonproductive periods were identified via an operative questionnaire survey. The three highest ranking problems impairing craftsmen's productivity were lack of materials, inadequate tools and work repetition.     

Measuring traffic lane‐changing by converting video into space–time still images

Empirical data is needed in order to extend our knowledge of traffic behavior. Video recordings are used to enrich typical data from loop detectors. In this context, data extraction from videos becomes a challenging task. Setting automatic video processing systems is costly, complex, and the accuracy achieved is usually not enough to improve traffic flow models. In contrast “visual” data extraction by watching the recordings requires extensive human intervention. A semiautomatic video processing methodology to count lane‐changing in freeways is proposed. The method allows counting lane changes faster than with the visual procedure without falling into the complexities and errors of full automation. The method is based on converting the video into a set of space–time still images, from where to visually count. This methodology has been tested at several freeway locations near Barcelona (Spain) with good results. A user‐friendly implementation of the method is available on http://bit.ly/2yUi08M .     

Heuristic solution using decision tree model for enhanced XML schema matching of bridge structural calculation documents

Research on the quality of data in a structural calculation document (SCD) is lacking, although the SCD of a bridge is used as an essential reference during the entire lifecycle of the facility. XML Schema matching enables qualitative improvement of the stored data. This study aimed to enhance the applicability of XML Schema matching, which improves the speed and quality of information stored in bridge SCDs. First, the authors proposed a method of reducing the computing time for the schema matching of bridge SCDs. The computing speed of schema matching was increased by 13 to 1800 times by reducing the checking process of the correlations. Second, the authors developed a heuristic solution for selecting the optimal weight factors used in the matching process to maintain a high accuracy by introducing a decision tree. The decision tree model was built using the content elements stored in the SCD, design companies, bridge types, and weight factors as input variables, and the matching accuracy as the target variable. The inverse-calculation method was applied to extract the weight factors from the decision tree model for high-accuracy schema matching results.     

Decision tree for selecting retaining wall systems based on logistic regression analysis

Machine learning techniques generally require thousands of cases to derive a reliable conclusion, but such a large number of excavation cases are very difficult to acquire in the construction domain. There have been efforts to develop retaining wall selection systems using machine learning techniques but based only on a couple of hundred cases of excavation work. The resultant rules were inconsistent and unreliable. This paper proposes an improved decision tree for selecting retaining wall systems. After retaining wall systems were divided into three components, i.e., the retaining wall, the lateral support, and optional grouting, a series of logistic regression analyses, analysis of variance (ANOVA), and chi-square tests were used to derive the variables and a decision tree for selecting retaining wall systems. The prediction accuracy rates for the retaining walls, lateral supports, and grouting were 82.6%, 80.4%, and 76.9%, respectively. These values were higher than the prediction accuracy rate (58.7%) of the decision tree built by an automated machine learning algorithm, Classification and Regression Trees (CART), with the same data set.     

Travel and activity choices based on an individual accessibility model

An individuals travel and activity behaviour is influenced by temporal and spatial constraints, travel and activity characteristics and individual attributes. This article formulates an individual accessibility model to measure the accessibility benefits of daily activities undertaken through a trip, a trip chain or at home. The model is extended further to analyse individuals activity location choices, choices between activities at home and activities through travel, and activity timing and scheduling decisions, with the assumption that an individual chooses an activity/travel alternative with the maximum accessibility benefits. An individuals choice among different locations for participating in an activity is shown to depend on the time budget and the locations of activities scheduled before and after this decided activity. The substitution of an activity at home for an activity through travel is shown to depend on the relative magnitude of activity location attraction and activity duration between these two types of activities and preference parameters. Finally, the article illustrates how an individual schedules one or several continuous or discontinuous activities with time-dependent accessibility benefits so as to maximise benefits.Received: 12 June 2001, Accepted: 1 November 2002, JEL Classification: D11, R22, R40The authors would like to thank the National Science Council, R.O.C., for financially supporting this research under grant NSC 89-2211-E-009-077.     

决策树法在投标中的应用

介绍了决策树法的原理、决策步骤 ,举例说明了决策树法在施工投标中的应用。证明了决策树法作为成熟的定量分析方法 ,简单可行 ,易于操作 ,增加了招投标决策工作的科学性。     

Roadway Asset Inspection Sampling Using High‐Dimensional Clustering and Locality‐Sensitivity Hashing

A high‐dimensional clustering‐based sampling method for roadway asset condition inspection is proposed in this study. The method complements existing literature by selecting sample roadway segments that contain multiple types of assets (e.g., signage, shoulder work, pavement marking, etc.) for the accurate estimation of their respective level of maintenance (LOMs). This is consistent with the standard maintenance procedure as inspection activities are often conducted on roadway segment basis. The proposed method consists of three components: current condition estimation, similarity matrix construction, and stratification. Current condition estimation predicts assets’ “current condition” by considering historical inspection records. Similarity matrix construction represents the core piece of the sampling framework, which employs locality‐sensitive hashing algorithm to define the similarity between segments. The stratification process is implemented with spectral clustering, which assigns segments into clusters based on the similarity matrix. The proposed method outperforms simple random sampling, which is widely used in practice, especially under the circumstances where LOM varies greatly across assets. The main highlight of the proposed method is the ability to select sample segments with multiple types of assets that are representative of their respective LOMs of the full inventory, which directly translates into an efficient maintenance activity management. The method is implemented using asset inspection records in the state of Utah from September, 2014 to March 2016. It represents a potentially useful tool for agencies to effectively conduct asset inspection and can be easily adopted for choosing samples containing multiple features.     

劲性桩加预应力锚杆支护结构在深基坑工程中的应用

通过徽商广场工程实例,介绍了劲性桩加预应力锚杆支护结构的设计、施工工艺和试验与监测情况,有效解决了施工的难点问题,总结出施工技术经验,以便类似工程参考应用.     

On a group utility function for siting a nuclear power plant

A method of group decision making for selecting the optimum location for a nuclear power plant is considered. A concept of convex dependence among three decision makers, an electric power company, the users of electricity, and the population of the region is described using a hypothetical problem. It is shown that convex dependence would play an important role in the group decision or the society's decision, since by using this concept it is possible to describe the different preference structure of each decision maker which depends on the utility level (degree of satisfaction) of the other decision makers.     

A multicriteria approach to support the location of thalassotherapy (seawater therapy) resorts: Application to Galicia region, NW Spain

This paper proposes a methodology for the location of thalassotherapy resorts to promote sustainable tourism in Galicia, NW Spain. Thalassotherapy is the medical use of seawater and the marine environment as a form of therapy. The proposed methodology is based on a multicriteria evaluation approach that integrates the economic, environmental and social factors that determine the best locations for this activity. A Geographical Information System is used to manage evaluation data and to visualize the results. A total of 211 potential sites were identified, from which 19 suitable locations were selected by applying a conjunctive method based on five criteria. The suitable sites were ranked from the point of view of different stakeholders using a multicriteria evaluation procedure. Results show that the ranking of alternative sites for thalassotherapy resorts is different for promoters, clients and Administration insofar as it is strongly influenced by the weighting of criteria. Accordingly, the proposed multicriteria approach can help stakeholders select the best site according to their interests or objectives and analyze the consequences of the decisions made.     

模糊模式识别在建设选址决策中的应用

根据模糊模式识别构建了建设项目选址的一般数学模型,并根据最大隶属原则提出了求解方法及其应用示例,以提高决策的科学性和可靠性。