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This research aims to develop an automated and optimization algorithms (OAs)-integrated 4D building information modeling (BIM) approach and a prototype and enable construction managers and practitioners to estimate the time of compound elements in building projects using the resource specification technique.

A 4D BIM estimation process was first developed by applying the resource specification and geometric information from the BIM model. A suite of OA including particle swarm optimization, ant colony, differential evolution and genetic algorithm were developed and compared in order to facilitate and automate the estimation process. The developed processes and porotypes were linked and integrated.

The OA-based automated 4D BIM estimation prototype was developed and validated through a real-life construction project. Different OAs were applied and compared, and the genetic algorithm was found as the best performing one. The prototype was successfully linked with BIM timeliner application. By using this approach, the start and finish dates of all object-based activities are developed, and the project completion time is automatically estimated.

Unlike conventional construction estimation methods which need various tools and are error prone and time-consuming, the developed method bypasses the existing time estimation tools and provides the integrated and automated process with BIM and machine learning algorithms. Furthermore, this approach integrates 4D BIM applications into construction design procedures, connected with OA automation.

In estimating budgetary needs, public managers focus on the major elements in delivery of public services, resources, work, and objectives/results. The flow of reasoning is backward along the process of service delivery--from objectives, to the work plan, to resource requirements. This understanding or model of budgeting, called “the logic of estimation,” is prominent in budgetary texts and other public administration literature, but it deserves additional attention and elaboration. Such effort at new attention shows the origins and development of the model in the public administration literature of the last half century, and the literature of an even longer period provides further concepts and measures by which the manager estimates. This new attention and elaboration holds benefits for teaching, research, and practice alike, and the current efforts toward results-oriented budgeting make it especially appropriate today.

Accurate estimation or prediction of the resource required for a project is very important for construction. The more accurate the prediction model, the greater the potential for cost savings will be through elimination of any redesign and the minimization of the maintenance expenses. Contractors can also make use of the models for last‐minute bid estimation. In the past the estimators perform the task by analogy with similar previous projects. This approach highly relies on their experience and knowledge. Owing to the lack of a scientific and easily apprehensible method in resource estimation, prediction outcomes are mainly based on humans’ perception, which is inconsistent and exhibits large variations. This paper proposes the use of multiple Group Method of Data Handling (GMDH) models in developing models for resource estimation. The illustrative example has demonstrated the high accuracy of the approach which is superior to other architectures based on artificial neural networks.

Current industry practices illustrate there is no standard method to estimate the number of hours worked on maintenance activities; instead, industry experts use experience to guess maintenance work hours. There is also a gap in the research literature on maintenance work hour estimation. This paper investigates the use of machine-learning algorithms to predict maintenance work hours and proposes a method that utilizes historical preventive maintenance order data to predict maintenance work hours.

The paper uses the design research methodology utilizing a case study to validate the proposed method.

The case study analysis confirms that the proposed method is applicable and has the potential to significantly improve work hour prediction accuracy, especially for medium- and long-term work orders. Moreover, the study finds that this method is more accurate and more efficient than conducting estimations based on experience.

The study has major implications for industrial applications. Maintenance-intensive industries such as oil and gas and chemical industries spend a huge portion of their operational expenditures (OPEX) on maintenance. This research will enable them to accurately predict work hour requirements that will help them to avoid unwanted downtime and costs and improve production planning and scheduling.

The proposed method provides new insights into maintenance theory and possesses a huge potential to improve the current maintenance planning practices in the industry.

The aim of this paper is to provide a general overview of the global oil and natural gas resources, production, technology development, energy use, emissions and costs. The activity is based on the European project “Risk of Energy Availability: Common Corridors for Europe Supply Security” (REACCESS) and the data collected was used in this project as an input to evaluate the technical, economical and environmental characteristics of the energy corridors to European Union (EU).

The paper is based on literature reviews and data collection from national authorities, oil companies, international associations and international organisations.

The work provides a general overview of oil and natural gas resources, production rates, recent technology developments, costs, losses, energy consumption and emissions on a world regional level. Main issues related to the role of conventional oil and natural gas in the energy import framework are summarised in this paper.

The present study provides information on conventional oil and natural gas resources and it is limited to primary production technologies.

An outline of oil and natural gas on a regional level is presented. The paper provides general introduction to the subject and it is a valuable input for modelling and analyses of conventional oil and natural gas in the present and in the future energy system.

The purpose of this article is to present a model to estimate and evaluate the operational costs of alternative layouts for large capacity warehouses or distribution centers with a large variety of goods.

The proposed model is based on time and resources studies per each of the basic activities on a warehouse operation. For validation purposes, the proposed model was applied on a perishable goods warehouse in Mexico. The output data was compared to actual data. Performance measures were operational costs and average picking time.

It was found that the proposed model is robust, flexible, simple and easy to be implemented. The model was used to evaluate two new alternatives of layout and operations of the same warehouse. It was found that the option with the layout with docks on long opposite sides of the warehouse and the operation without a separate picking zone minimizes operational costs.

The richness of the model is strongly supported by the information the warehouse has about its operation. With knowledge of the process, it is required to distinguish deterministic from stochastic basic activities and develop distance computations that depend on the layout being studied.

The approach used to model warehouse operations was to estimate the movements and resource consumption per commodity. This allows the model to be used in every operational context when the complexity of the system is strongly dependent on and proportional to the volume of operations. In addition, it is particularly adequate as a tool to compare average performance measures of different scenarios for the same system.

The model proposed here provides a simple way to estimate particularly operational resource consumptions and picking times as proxy measures for efficiency and efficacy of a warehouse. It uses distance computations, time information and unit occurrence frequencies of basic activities over a single commodity in the system.

Although preference for sons has been documented among parents in developing countries, it is an open question whether and to what extent intra-household resource allocation is influenced by family sex composition. This study investigates the effects of sex composition on intra-household resource allocation based on the collective household model of Dunbar, Lewbel, and Pendakur (2013). I extend their model to estimate the influences on a household member’s resource share by observing how budget shares of a private assignable good vary not only with total expenditure and family size, but also with family sex composition. Using data from the 2005 Iranian Household Income and Expenditure Survey, I find that family composition significantly affects intra-household resource allocation in Iranian rural areas. Specifically, rural parents assign 1.6–1.9 percentage points more resources toward their sons. These resources are essentially coming at the expense of mothers. In all-boy families, mothers get 2.8–3.6 percentage points fewer resources than they do in all-girl families. These effects are more pronounced among farmer families than nonfarmer families. However, I find no significant role for gender composition in intra-household resource allocation in urban areas.

Internet has changed radically in the way people interact in the virtual world, in their careers or social relationships. IoT technology has added a new vision to this process by enabling connections between smart objects and humans, and also between smart objects themselves, which leads to anything, anytime, anywhere, and any media communications. IoT allows objects to physically see, hear, think, and perform tasks by making them talk to each other, share information and coordinate decisions. To enable the vision of IoT, it utilizes technologies such as ubiquitous computing, context awareness, RFID, WSN, embedded devices, CPS, communication technologies, and internet protocols. IoT is considered to be the future internet, which is significantly different from the Internet we use today. The purpose of this paper is to provide up-to-date literature on trends of IoT research which is driven by the need for convergence of several interdisciplinary technologies and new applications.

A comprehensive IoT literature review has been performed in this paper as a survey. The survey starts by providing an overview of IoT concepts, visions and evolutions. IoT architectures are also explored. Then, the most important components of IoT are discussed including a thorough discussion of IoT operating systems such as Tiny OS, Contiki OS, FreeRTOS, and RIOT. A review of IoT applications is also presented in this paper and finally, IoT challenges that can be recently encountered by researchers are introduced.

Studies of IoT literature and projects show the disproportionate importance of technology in IoT projects, which are often driven by technological interventions rather than innovation in the business model. There are a number of serious concerns about the dangers of IoT growth, particularly in the areas of privacy and security; hence, industry and government began addressing these concerns. At the end, what makes IoT exciting is that we do not yet know the exact use cases which would have the ability to significantly influence our lives.

This survey provides a comprehensive literature review on IoT techniques, operating systems and trends.

In the current era of Industry 4.0, the manufacturing industries are striving toward mass production with mass customization by considering human–robot collaboration. This study aims to propose the reconfiguration of assembly systems by incorporating multiple humans with robots using a human–robot task allocation (HRTA) to enhance productivity.

A human–robot task scheduling approach has been developed by considering task suitability, resource availability and resource selection through multicriteria optimization using the Linear Regression with Optimal Point and Minimum Distance Calculation algorithm. Using line-balancing techniques, the approach estimates the optimum number of resources required for assembly tasks operating by minimum idle time.

The task allocation schedule for a case study involving a punching press was solved using human–robot collaboration, and the approach incorporated the optimum number of appropriate resources to handle different types of proportion of resources.

This proposed work integrates the task allocation by human–robot collaboration and decrease the idle time of resource by integrating optimum number of resources.

Project schedules have a vital role in the effective management of time, cost, scope and resources in construction projects, and creating schedules requires schedulers with construction knowledge and experience. The increase in the complexity of building projects and the emergence of building information modeling (BIM) in the architecture, engineering and construction industry have encouraged researchers to explore BIM capabilities for automated schedule generation. The scope and capabilities of the developed systems, however, are limited and the link between design and scheduling is still underdeveloped. This paper aims to investigate methods to develop a BIM-based framework to automatically generate schedules for concrete-framed buildings.

This system first extracts the required data from the building information model, including elements’ dimensions, quantities, spatial information, materials and other related attributes. It then applies construction rules, prior knowledge and production rate data to create project work-packages, calculate their durations and determine their relationships. Finally, it organizes these results into a schedule using project management software.

This system provides an automated and easy-to-use approach to generate schedules for concrete-framed buildings that are modeled in a BIM platform. It provides two schedules for each project, both a sequential and an overlapped solution, which the schedulers can modify into a practical schedule based on conditions and available resources.

This research project presents an innovative approach to use BIM-based attributes of structural elements to develop list of work-packages and estimate their durations, and then it uses a combination of rule-based and case-based reasoning to generate the schedules.