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The purpose of this paper is to synthesize and characterize nano-ceramic blue pigment Co_0.5Zn_0.5Al₂O₄ via polyacrylamide gel method. Generally, the high cost and the environmental toxicity of cobalt aluminate pigments lead them to become less common and cause problems in production process. To significantly reduce this problem, it is required to reduce the cobalt in the pigment and replace the cobalt with some amounts of zinc in the structure.

In this paper, calcination temperature and its effects on phase specification and color properties of final product were investigated. The powders were studied by using XRD, FESEM, TG/DTA, FTIR, UV-Vis and colorimetric in CIELab space, in which the calcination temperatures were set to 600°C, 800°C and 1,000 °C, and the inert atmosphere was air.

According to the XRD patterns, single-phase spinel structure with a good crystallinity was formed even in the low temperature. The infrared spectra displayed vibrations at about 500, 560 and 680 cm⁻¹, which were ascribed to the spinel structure. FESEM images showed nanoscale particles with an average size of 32 nm. Regarding the Co²⁺ spin transitions in tetrahedral sites, the UV-Vis spectra presented three bands at 552, 598 and 628 nm.

The colorimetric data indicated the formation of blue pigments corresponding to negative values of b*. The color of pigments was affected by calcination temperature.

The characterization analysis shows that a blue pigment has been obtained in this research. Different degrees of blue color were obtained at different calcination temperatures.

This study aims to investigate the relationship between information technology and internal controls of state agencies in Iran.

The research population includes all auditors and managers working in public sector. Data collection instrument is a questionnaire designed by the researcher and administrated during March 5, 2016. The collected data are analyzed through descriptive and inferential statistics (binomial test).

The findings of the research show that there is a significant relationship between information technology and internal controls (administrative, financial and accounting controls, risk assessment, information and communication, control activities and monitoring). Moreover, the alteration of data collection methods (from traditional to modern) and the written instructions (in information technology) have a positive effect on the internal control and its subscales.

With regard to the emphasis on the development of computer application and the use of new processing facilities and the exchange of information and its specific controlling consequences, this is an innovative research.

Computer vision (CV) offers a promising approach to transforming the conventional in-person inspection practices prevalent within the construction industry. However, the reliance on centralized systems in current CV-based inspections introduces a vulnerability to potential data manipulation. Unreliable inspection records make it challenging for safety managers to make timely decisions to ensure safety compliance. To address this issue, this paper proposes a blockchain (BC) and CV-based framework to enhance safety inspections at construction sites.

This study adopted a BC-enhanced CV approach. By leveraging CV and BC, safety conditions are automatically identified from site images and can be reliably recorded as safety inspection data through the BC network. Additionally, by using this data, smart contracts coordinate inspection tasks, assign responsibilities and verify safety performance, managing the entire safety inspection process remotely.

A case study confirms the framework’s applicability and efficacy in facilitating remote and reliable safety inspections. The proposed framework is envisaged to greatly improve current safety inspection practices and, in doing so, contribute to reduced accidents and injuries in the construction industry.

This study provides novel and practical guidance for integrating CV and BC in construction safety inspection. It fulfills an identified need to study how to leverage CV-based inspection results for remotely managing the safety inspection process using BC. This work not only takes a significant step towards data-driven decision-making in the safety inspection process, but also paves the way for future studies aiming to develop tamper-proof data management systems for industrial inspections and audits.

The purpose of this research is to explore how to visually represent human decision-making processes during the performance of indoor building inspection flight operations using drones.

Data from expert pilots were collected using a virtual reality drone flight simulator. The expert pilot data were studied to inform the development of an interactive 2D representation of drone flight spatial and temporal data – InDrone. Within the InDrone platform, expert pilot data were visually encoded to characterize key pilot behaviors in terms of pilots' approaches to view and difficulties encountered while detecting the inspection markers. The InDrone platform was evaluated using a user-center experimental methodology focusing on two metrics: (1) how novice pilots understood the flight approaches and difficulties contained within InDrone and (2) the perceived usability of the InDrone platform.

The results of the study indicated that novice pilots recognized inspection markers and difficult-to-inspect building areas in 63% (STD = 48%) and 75% (STD = 35%) of the time on average, respectively. Overall, the usability of InDrone presented high scores as demonstrated by the novice pilots during the flight pattern recognition tasks with a mean score of 77% (STD = 15%).

This research contributes to the definition of visual affordances that support the communication of human decision-making during drone indoor building inspection flight operations. The developed InDrone platform highlights the necessity of defining visual affordances to explore drone flight spatial and temporal data for indoor building inspections.

Ready-mix concrete delivery problem (RMCDP), a specific version of the vehicle routing problem (VRP), is a relevant supply-chain engineering task for construction management with various formulations and solving methods. This problem can range from a simple scenario involving one source, one material and one destination to a more challenging and complex case involving multiple sources, multiple materials and multiple destinations. This paper presents an Internet of Things (IoT)-supported active building information modeling (BIM) system for optimized multi-project ready-mix concrete (RMC) delivery.

The presented system is BIM-based, IoT supported, dynamic and automatic input/output exchange to provide an optimal delivery program for multi-project ready-mix-concrete problem. The input parameters are extracted as real-time map-supported IoT data and transferred to the system via an application programming interface (API) into a mixed-integer linear programming (MILP) optimization model developed to perform the optimization. The obtained optimization results are further integrated into BIM by conventional project management tools. To demonstrate the features of the suggested system, an RMCDP example was applied to solve that included four building sites, seven eligible concrete plants and three necessary RMC mixtures.

The system provides the optimum delivery schedule for multiple RMCs to multiple construction sites, as well as the optimum RMC quantities to be delivered, the quantities from each concrete plant that must be supplied, the best delivery routes, the optimum execution times for each construction site, and the total minimal costs, while also assuring the dynamic transfer of the optimized results back into the portfolio of multiple BIM projects. The system can generate as many solutions as needed by updating the real-time input parameters in terms of change of the routes, unit prices and availability of concrete plants.

The suggested system allows dynamic adjustments during the optimization process, andis adaptable to changes in input data also considering the real-time input data. The system is based on spreadsheets, which are widely used and common tool that most stakeholders already utilize daily, while also providing the possibility to apply a more specialized tool. Based on this, the RMCDP can be solved using both conventional and advanced optimization software, enabling the system to handle even large-scale tasks as necessary.

Blockchain technology (BCT) is considered a promising tool to improve the productivity of construction project management. Existing research has studied its potential costs and benefits for the construction industry. However, the potential costs and benefits of BCT failed to be compared as actual costs and benefits of specific applications for stakeholders. To fill this gap, this study seeks to analyze the cost-effectiveness of BCT-based applications in construction project management.

This study is conducted with a customized systematic literature review based on transaction cost theory to enable qualitative comparison. With a deliberately designed structure confining extraneous variables, the costs and benefits of BCT-based applications are identified and compared. The inherent dependent relations of processes and the evolution relations of functions are identified. The cost-effectiveness of blockchain adoption is then analyzed.

Seven functions and six challenges are identified within five processes. The result suggests all identified functions are cost-effective except for manual instruction (coding smart contracts manually). The smart contracts require explicit definition and logic to be effective. However, the construction projects essentially require the institution to be flexible due to unpredictability. The adoption of smart contracts and corresponding additional requirements can increase the transaction cost of bounded rationality.

As manual instruction is fundamental to realize other functions, and its advanced substitute relies on its broad adoption, its cost-effectiveness must be improved for applications to be acceptable to stakeholders. The establishment of a universal smart contract model and a universal, legitimate and efficient database structure are recommended to minimize the cost and maximize the effect of applications.

This study contributes to the knowledge by providing a comprehensive analysis of BCT adoption’s cost-effectiveness in construction project management. The adopted review structure can be extended to analyze the qualitative benefits and challenges of management automation in the early stages.

Traditional central courtyards have been advocated for being thermally efficient for hot-climate regions. However, exploring previous literature shows that it is not clear to what extent courtyards are truly thermally comfortable. This study determines the level of thermal comfort in residential courtyards in hot-climate regions, taking Baghdad as a case study.

This study develops a novel Courtyard Thermal Usability Index (CTUI) to quantify the ability of courtyards to provide thermal comfort to occupants. CTUI is the fraction of useable thermally comfortable hours in courtyards of the total occupation hours during a specific period. To operationalise CTUI, the research employs the Envi-met 4.2 simulation tool to determine the annual thermal conditions of 360 courtyards. An adaptive thermal comfort model developed by Al-Hafith in 2020 for Iraq is used to judge simulated thermal conditions and determine CTUI.

CTUI enables determining the level of thermal comfort courtyards offer to occupants by showing the ratio of the thermally comfortable period versus the occupation period. Results show that, in Iraq, annually, courtyards offer up to 38% comfortable hours out of the total potential occupation hours. The rest of the time the courtyard will not be comfortable, mostly due to overheating. When designing courtyards, the most effective geometric property impacting courtyards' thermal conditions is width/height. The most important microclimatic factor impacting occupants' thermal sensation is mean radiant temperature (MRT). This study can be used to inform designing thermally efficient courtyards for hot-climate regions.

This study presents the first assessment of the thermal efficiency of courtyards in hot-climate regions depending on an assessment of their ability to provide thermal comfort to occupants. The study presents a novel index that can be used to quantify the ability of courtyards to provide a thermally comfortable environment to occupants.

Previous research has demonstrated that Digital Twins (DT) are extensively employed to improve sustainable construction methods. Nonetheless, their uptake in numerous nations is still constrained. This study seeks to identify and examine the digital twin’s implementation barriers in construction building projects to augment operational performance and sustainability.

An iterative two-stage approach was adopted to explore the phenomena under investigation. General DT Implementation Barriers were first identified from extant literature and subsequently explored using primary questionnaire survey data from Hong Kong building industry professionals.

Survey results illustrated that Lack of methodologies and tools, Difficulty in ensuring a high level of performance in real-time communication, Impossibility of directly measuring all data relevant to the DT, need to share the DT among multiple application systems involving multiple stakeholders and Uncertainties in the quality and reliability of data are the main barriers for adopting digital twins' technology. Moreover, Ginni’s mean difference measure of dispersion showed that the stationary digital twin’s barriers adoption is needed to share the DT among multiple application systems involving multiple stakeholders.

The study’s findings offer valuable guidance to the construction industry. They help stakeholders adopt digital twins' technology, which, in turn, improves cost efficiency and sustainability. This adoption reduces project expenses and enhances environmental responsibility, providing companies a competitive edge in the industry.

This research rigorously explores barriers to Digital Twin (DT) implementation in the Hong Kong construction industry, employing a systematic approach that includes a comprehensive literature review, Ranking Analysis (RII) and Ginni’s coefficient of mean difference (GM). With a tailored focus on Hong Kong, the study aims to identify, analyze and provide novel insights into DT implementation challenges. Emphasizing practical relevance, the research bridges the gap between academic understanding and real-world application, offering actionable solutions for industry professionals, policymakers and researchers. This multifaceted contribution enhances the feasibility and success of DT implementation in construction projects within the Architecture, Engineering and Construction (AEC) sector.

Blockchain is a developing technology that affects numerous industries, including facility management (FM). Many barriers are associated with adopting blockchain-enabled building information modeling (BEBIM) in FM. This research aims to identify and prioritize the barriers to adopting BEBIM in FM.

To address the knowledge gap, this study employs a two-phase methodology for evaluating the barriers to adopting BEBIM in FM. The first phase involves a comprehensive literature review identifying 14 barriers to BEBIM adoption. Using a Delphi approach, the identified barriers were categorized into 6 groups and finalized by 11 experts, adding 3 more barriers to the list. The best-worst method (BWM) determines the priority weights of identified barriers and sub-barriers in the second phase.

This study reveals that adopting BEBIM for FM in India faces significant hurdles. The most critical barriers are “limited collaboration” and “communication among stakeholders,” “legal constraints in certain jurisdictions” and “challenges in establishing trust and governance models.” To mitigate these barriers, stakeholders should foster collaboration and communication, develop efficient blockchain technology (BT) and establish a trust and governance model.

This work underscores the importance of formulating effective strategies to overcome the identified barriers and emphasizes implications that can assist policymakers and industry stakeholders in achieving successful BEBIM adoption for improved FM practice.

The study provides valuable insights for policymakers, construction industry stakeholders and facility managers interested in leveraging this technology to improve the efficiency and effectiveness of FM practice in India.

The smart contract provides an opportunity to improve existing contract management practices in the construction projects by replacing traditional contracts. However, translating the contracts into computer languages is considered a major challenge which has not been investigated. Thus, it is necessary to: (1) identify the obstructing clauses in real-world contracts; and (2) analyze the replacement's technical and economic feasibility. This paper aims to discuss the aforementioned objectives.

This study identified the flexibility clauses of traditional contracts and their corresponding functions through inductive content analysis with representative standard contracts as materials. Through a speculative analysis in accordance to design science paradigm and new institutional economics, the economic and technical feasibility of existing approaches, including enumeration method, fuzzy algorithm, rough sets theory, machine learning and artificial intelligence, to transform respective clauses (functions) into executable codes are analyzed.

The clauses of semantic flexibility and structural flexibility are identified from the contracts. The transformation of semantic flexibility is economically and/or technically infeasible with existing methods and materials. But with more data as materials and methods of rough sets or machine learning, the transformation can be feasible. The transformation of structural flexibility is technically possible however economically unacceptable.

Given smart contracts' inability to provide the required flexibility for construction projects, smart contracts will be more effective in less relational contracts. For construction contracts, the combination of smart contracts and traditional contracts is recommended. In the long run, with the sharing or trading of data in the industry level and the integration of machine learning or artificial intelligence reducing relevant costs, the automation of contract management can be achieved.

This study contributes to the understanding of the smart contract's limitations in industry scenarios and its role in construction project management.