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Rebar is the prime component of reinforced concrete structures, and rebar monitoring is a time-consuming and technical job. With the emergence of the fourth industrial revolution, the construction industry practices have evolved toward digitalization. Still, hesitation remains among stakeholders toward the adoption of advanced technologies and one of the significant reasons is the unavailability of knowledge frameworks and implementation guidelines. This study aims to investigate technical factors impacting automated monitoring of rebar for the understanding, confidence gain and effective implementation by construction industry stakeholders.

A structured study pipeline has been adopted, which includes a systematic literature collection, semistructured interviews, pilot survey, questionnaire survey and statistical analyses via merging two techniques, i.e. structural equation modeling and relative importance index.

The achieved model highlights “digital images” and “scanning” as two main categories being adopted for automated rebar monitoring. Moreover, “external influence”, “data-capturing”, “image quality”, and “environment” have been identified as the main factors under “digital images”. On the other hand, “object distance”, “rebar shape”, “occlusion” and “rebar spacing” have been highlighted as the main contributing factors under “scanning”.

The study provides a base guideline for the construction industry stakeholders to gain confidence in automated monitoring of rebar via vision-based technologies and effective implementation of the progress-monitoring processes. This study, via structured data collection, performed qualitative and quantitative analyses to investigate technical factors for effective rebar monitoring via vision-based technologies in the form of a mathematical model.

This paper aims to look at unpatched software which represents a significant problem for internet‐based systems, with a myriad malware incidents and hacker exploits taking advantage of vulnerable targets. Unfortunately, vulnerability management is a non‐trivial task, and is complicated by an increasing number of vulnerabilities and the workload implications associated with handling the associated security advisories and updates.

As a step towards addressing the problem, this paper presents an automated framework that is designed to provide a vendor‐independent means of vulnerability notification and rectification for system administrators.

In the proposed framework, incoming vulnerability advisory messages may be obtained from multiple sources, and then filtered and prioritised according to the specific requirements of the target environment (as determined by the security administrator). In addition to notification management, the framework provides an automated facility for the download and deployment of any associated patches. The framework has been implemented in prototype form, with particular focus on the notification manager.

This paper presents an automated framework, providing a valuable and comprehensive solution for managing vulnerabilities in terms of notification and rectification systems.

The purpose of this paper is to propose a framework for security controls automation, in order to achieve greater efficiency and reduce the complexity of information security management.

This research reviewed the controls recommended by well known standards such as ISO/IEC 27001 and NIST SP 800‐53; and identified security controls that can be automated by existing hard‐and software tools. The research also analyzed the Security Information and Event Management (SIEM) technology and proposed a SIEM‐based framework for security controls automation, taking into account the automation potential of SIEM systems and their integration possibilities with several security tools.

About 30 per cent of information security controls can be automated and they were grouped in a list of ten automatable security controls. A SIEM‐based framework can be used for centralized and integrated management of the ten automatable security controls.

By implementing the proposed framework and therefore automating as many security controls as possible, organizations will achieve more efficiency in information security management, reducing also the complexity of this process. This research may also be useful for SIEM vendors, in order to include more functionality to their products and provide a maximum of security controls automation within SIEM platforms.

This paper delimits the boundaries of information security automation and defines what automation means for each security control. A novel framework for security controls automation is proposed. This research provides an automation concept that goes beyond what it is normally described in previous works and SIEM solutions.

This paper proposes an innovative intelligent simulation-based construction planning framework that introduces a new approach to simulation-based construction planning.

In this approach, the authors developed an ontological inference engine as an integrated part of a constraint-based simulation system that configures the construction processes, defines activities and manages resources considering a variety of requirements and constraints during the simulation. It allows for the incorporation of the latest project information and a deep level of construction planning knowledge in the planning. The construction planning knowledge is represented by an ontology and several semantic rules. Also, the proposed framework uses the project building information model (BIM) to extract information regarding the construction product and the relations between elements. The extracted information is then converted to an ontological format to be useable by the framework.

The authors implemented the framework in a case study project and tested its usefulness and capabilities. It successfully generated the construction processes, activities and required resources based on the construction product, available resources and the planning rules. It also allowed for a variety of analyses regarding different construction strategies and resource planning. Moreover, 4D BIM models that provide a very good understanding of the construction plan can be automatically generated using the proposed framework.

The active integration between BIM, discrete-event simulation (DES) and ontological knowledge base and inference engine defines a new class of construction simulation with expandable applications.

Analyzing different scenarios at the design stage of construction projects has always been a challenging task. One of the main parameters that helps owners in making better decisions in designing their buildings is to look after the cost perspective on different design scenarios. Thus, this study aims to propose a semi-automated BIM-based cost estimation approach that enables practitioners to estimate the cost of projects based on different design scenarios by an accurate and agile system.

This study proposes an integrated framework, through which the cost estimation standard of Iran (FehrestBaha) is linked to the materials quantity take-offs (QTO) from BIM models. The performance of the system is based on connecting the classification standards of UniFormat and MasterFormat to the cost estimation standard of FehrestBaha. A BIM-based extension in the Revit environment is developed to automate the cost estimation process.

To evaluate the efficiency of the proposed approach in cost estimation, it is implemented to estimate the cost of the architectural discipline in a real construction project. The results indicate that the proposed BIM-based approach estimated the cost of the architectural discipline with an acceptable level of accuracy.

The proposed approach could be used by practitioners to have an agile and accurate BIM-based cost estimation of different scenarios during design process. The semi-automated system considerably reduces the time of cost estimation in comparison to the traditional manual approaches, particularly in complex structures. Owners are able to easily trace changes in project cost according to any changes in components and materials of the BIM model. Furthermore, the proposed approach provides a practical roadmap for BIM-based cost estimation based on cost estimation standards in different countries.

Unlike the traditional manual cost estimation approaches, the proposed BIM-based approach is not highly dependent on the knowledge of experienced estimators, which therefore facilitates its implementation. Furthermore, automating both QTO process and the required calculations in this approach increases the accuracy of cost estimation while decreasing the probability of human errors or omission occurrence.

Higher energy conversion efficiency of internal combustion engine can be achieved with optimal control of unsteady in-cylinder flow fields inside a direct-injection (DI) engine. However, it remains a daunting task to predict the nonlinear and transient in-cylinder flow motion because they are highly complex which change both in space and time. Recently, machine learning methods have demonstrated great promises to infer relatively simple temporal flow field development. This paper aims to feature a physics-guided machine learning approach to realize high accuracy and generalization prediction for complex swirl-induced flow field motions.

To achieve high-fidelity time-series prediction of unsteady engine flow fields, this work features an automated machine learning framework with the following objectives: (1) The spatiotemporal physical constraint of the flow field structure is transferred to machine learning structure. (2) The ML inputs and targets are efficiently designed that ensure high model convergence with limited sets of experiments. (3) The prediction results are optimized by ensemble learning mechanism within the automated machine learning framework.

The proposed data-driven framework is proven effective in different time periods and different extent of unsteadiness of the flow dynamics, and the predicted flow fields are highly similar to the target field under various complex flow patterns. Among the described framework designs, the utilization of spatial flow field structure is the featured improvement to the time-series flow field prediction process.

The proposed flow field prediction framework could be generalized to different crank angle periods, cycles and swirl ratio conditions, which could greatly promote real-time flow control and reduce experiments on in-cylinder flow field measurement and diagnostics.

Erythemato-squamous disease (ESD) is one of the complex diseases related to the dermatology field. Due to common morphological features, the diagnosis of ESDs become stringent and leads to inconsistency. Besides, diagnosis has been done on the basis of inculcated visible symptoms pertinent with the expertise of the physician. Hence, ontology construction for ESD is essential to ensure credibility, consistency, to resolve lack of time, labor and competence and to diminish human error.

This paper presents the design of an automatic ontology framework through data mining techniques and subsequently depicts the diagnosis of ESD using the available knowledge- and rule-based system.

The rule language (Semantic Web Rule Language) and rule engine (Jess and Drools) have been integrated to explore the severity of the ESD and foresee the most appropriate class to be suggested.

In this paper, the authors identify the efficiency of the rule engine and investigate the performance of the computational techniques in predicting ESD using three different measures.

Primarily, the approach assesses transfer time for total number of axioms exported to rule engine (Jess and Drools) while the other approach measures the number of inferred axioms (process time) using the rule engine while the third measure calculates the time to translate the inferred axioms to OWL knowledge (execution time).

Activity sampling is a technique to monitor onsite labourers' time utilisation, which can provide helpful information for the management level to implement suitable labour productivity improvement strategies continuously. However, there needs to be a review paper that compiles research on activity sampling studies to give readers a thorough grasp of the research trend. Hence, this paper aims to investigate the activity sampling techniques applied in earlier research from the angles of activity categories formation, data collection methods and data analysis.

The method used in this paper is a systematic review guided by the PRISMA framework. The search was conducted in Scopus and Web of Science. The inclusion and exclusion criteria were applied, selecting 70 articles published between 2011 and 2022 for data extraction and analysis. The analysis method involved a qualitative synthesis of the findings from the selected articles.

Activity sampling is broadly divided into four stages: targeting trade, determining activity categories, data collection and data analysis. This paper divides the activity categories into three levels and classifies the data collection methods into manual observation, sensor-based activity sampling and computer vision-based activity sampling. The previous studies applied activity sampling for two construction management purposes: labour productivity monitoring and ergonomic safety monitoring. This paper also further discusses the scientific research gaps and future research directions.

This review paper contributes to the body of knowledge in construction management by thoroughly understanding current state-of-the-art activity sampling techniques and research gaps.

The purpose of this paper is to propose a warranty-based bilateral automated multi-issue negotiation approach.

A methodology for bilateral automated negotiation process is developed considering the targets such as warranty attractiveness, warranty cost, mean time between failures, spare parts cost to the end user over the useful life of the life. The negotiation methodology is explained using different cases of negotiation. The optimization for each negotiation step is carried out using genetic algorithm with elitism strategy.

The result after optimization indicates that the desired target values are achieved and manufacturer obtained desired profit margin.

Application of automated negotiation model is illustrated using a real life case of an automobile engine manufacturer. The proposed approach helps the manufacturer of any product to develop a methodology for carrying out the negotiation process. The approach also results into taking warranty-related decisions at the design stage.

This paper contributes in proposing a generalized methodology for warranty-based negotiation in which the negotiation is carried out between the manufacturer and the customer.

Testing business processes is crucial to assess the compliance of business process models with requirements. Automating this task optimizes testing efforts and reduces human error while also providing improvement insights for the business process modeling activity. The primary purposes of this paper are to conduct a literature review of Business Process Model and Notation (BPMN) testing and formal verification and to propose the Business Process Evaluation and Research Framework for Enhancement and Continuous Testing (bPERFECT) framework, which aims to guide business process testing (BPT) research and implementation. Secondary objectives include (1) eliciting the existing types of testing, (2) evaluating their impact on efficiency and (3) assessing the formal verification techniques that complement testing.

The methodology used is based on Kitchenham's (2004) original procedures for conducting systematic literature reviews.

Results of this study indicate that three distinct business process model testing types can be found in the literature: black/gray-box, regression and integration. Testing and verification approaches differ in aspects such as awareness of test data, coverage criteria and auxiliary representations used. However, most solutions pose notable hindrances, such as BPMN element limitations, that lead to limited practicality.

The databases selected in the review protocol may have excluded relevant studies on this topic. More databases and gray literature could also be considered for inclusion in this review.

Three main originality aspects are identified in this study as follows: (1) the classification of process model testing types, (2) the future trends foreseen for BPMN model testing and verification and (3) the bPERFECT framework for testing business processes.