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Vision‐based intelligent automation systems have been slow in finding a way to the food industry, mainly due to the conservative nature of the food processing industrial sector, and the unproven maturity of the required vision and automation technologies. Vision‐based systems should be convincingly robust, and fulfil the set performance requirements at a reasonable economic investment.

This study aims to introduce a methodology for optimal allocation of spinning reserves taking into account load, wind and solar generation by application of the univariate and bivariate parametric models, conventional intra and inter-zonal spinning reserve capacity as well as demand response through utilization of capacity outage probability tables and the equivalent assisting unit approach.

The method uses a novel approach to model wind power generation using the bivariate Farlie–Gumbel–Morgenstern probability density function (PDF). The study also uses the Bayesian network (BN) algorithm to perform the adjustment of spinning reserve allocation, based on the actual unit commitment of the previous hours.

The results show that the utilization of bivariate wind prediction model along with reserve allocation adjustment algorithm improve reliability of the power grid by 2.66% and reduce the total system operating costs by 1.12%.

The method uses a novel approach to model wind power generation using the bivariate Farlie–Gumbel–Morgenstern PDF. The study also uses the BN algorithm to perform the adjustment of spinning reserve allocation, based on the actual unit commitment of the previous hours.

The purpose of this paper is to review cases of artificial reefs built through additive manufacturing (AM) technologies and analyse their ecological goals, fabrication process, materials, structural design features and implementation location to determine predominant parameters, environmental impacts, advantages, and limitations.

The review analysed 16 cases of artificial reefs from both temperate and tropical regions. These were categorised based on the AM process used, the mortar material used (crucial for biological applications), the structural design features and the location of implementation. These parameters are assessed to determine how effectively the designs meet the stipulated ecological goals, how AM technologies demonstrate their potential in comparison to conventional methods and the preference locations of these implementations.

The overview revealed that the dominant artificial reef implementation occurs in the Mediterranean and Atlantic Seas, both accounting for 24%. The remaining cases were in the Australian Sea (20%), the South Asia Sea (12%), the Persian Gulf and the Pacific Ocean, both with 8%, and the Indian Sea with 4% of all the cases studied. It was concluded that fused filament fabrication, binder jetting and material extrusion represent the main AM processes used to build artificial reefs. Cementitious materials, ceramics, polymers and geopolymer formulations were used, incorporating aggregates from mineral residues, biological wastes and pozzolan materials, to reduce environmental impacts, promote the circular economy and be more beneficial for marine ecosystems. The evaluation ranking assessed how well their design and materials align with their ecological goals, demonstrating that five cases were ranked with high effectiveness, ten projects with moderate effectiveness and one case with low effectiveness.

AM represents an innovative method for marine restoration and management. It offers a rapid prototyping technique for design validation and enables the creation of highly complex shapes for habitat diversification while incorporating a diverse range of materials to benefit environmental and marine species’ habitats.

Human error is among the leading causes of construction-based accidents. Previous studies on the factors affecting human error are rather vague from the perspective of complex and changeable working environments. The purpose of this paper is to develop a dynamic causal model of human errors to improve safety management in the construction industry. A theoretical model is developed and tested through a case study.

First, the authors defined the causal relationship between construction and human errors based on the cognitive reliability and error analysis method (CREAM). A dynamic Bayesian network (DBN) was then developed by connecting time-variant causal relationships of human errors. Next, prediction, sensitivity analysis and diagnostic analysis of DBN were applied to demonstrate the function of this model. Finally, a case study of elevator installation was presented to verify the feasibility and applicability of the proposed approach in a construction work environment.

The results of the proposed model were closer to those of practice than previous static models, and the features of the systematization and dynamics are more efficient in adapting toward increasingly complex and changeable environments.

This research integrated CREAM as the theoretical foundation for a novel time-variant causal model of human errors in construction. Practically, this model highlights the hazards that potentially trigger human error occurrences, facilitating the implementation of proactive safety strategy and safety measures in advance.

The purpose of this paper is to provide useful implications for Korean export companies to adopt the smart technology to improve their performance in the era of industrial convergence with the interdisciplinary study between trade and technology management.

This study followed the five-stage procedure and methods. In the first stage, measurement items were developed in four performance factors: leaning and growth, internal process, customer and finance. In the second stage, data were collected by conducting two types of surveys: first, for Korean export companies that have adopted Radio frequency identification (RFID) to test the proposed model and analyze the performance and second, for RFID experts of industry-university R&D cooperation to measure the relative importance of factors and items. In the third stage, the model was verified with structural equation modeling. In the fourth stage, AHP was used to analyze the relative importance of factors and items. In the fifth stage, post-RFID adoption performance in Korean export companies was measured by a formula for the performance index. Through these five-stage procedure and methods, the final performance improvement strategies and practical implications are presented in the conclusion.

The framework finds that the total score of RFID post-adoption on company performance proved relatively low, which indicates that the effect of this technology on export companies’ performance is still unsatisfactory. And financial performance proved to be ‘top priority’ area, which requires the most urgent effort for improvement since its importance was higher than learning and growth, internal process and customer performance—but nonetheless its performance index was the lowest. This study finds that strategic decision making is required for adopting smart technology in the perspective of technology convergence to improve the performance of companies among heterogeneous industries.

Despite the significant results of this study alone, it also has limitations. Therefore, the direction of the future study is as follows: future research should focus on finding specific impact factors enhancing post-adoption of smart technologies including RFID performance by conducting empirical studies that identify the factors affecting post adoption of smart technologies rate directly or indirectly.

In the current global market environment, not only technological convergence in the same kind of industry but also industrial convergence in the different kinds of industries are essential to manufacturing and service companies including to export companies with perspective of Innovation. This study has the value as an interdisciplinary study to actually measure the performance of a company by industrial convergence through the theme of adoption of smart technology in export companies.

This paper aims to focus on the most popular technique nowadays, the use of microwave irradiation in organic synthesis; in a few years, most chemists will use microwave energy to heat chemical reactions on a laboratory scale. Also, many scientists use microwave technology in the industry. They have turned to microwave synthesis as a frontline methodology for their projects. Microwave and microwave-assisted organic synthesis (MAOS) has emerged as a new “lead” in organic synthesis.

Using microwave radiation for synthesis and design of fluorescent dyes is of great interest, as it decreases the time required for synthesis and the synthesized dyes can be applied to industrial scale.

The technique offers many advantages, as it is simple, clean, fast, efficient and economical for the synthesis of a large number of organic compounds. These advantages encourage many chemists to switch from the traditional heating method to microwave-assisted chemistry.

This review highlights applications of microwave chemistry in organic synthesis for fluorescent dyes. Fluorescents are a fairly new and very heavily used class of organics. These materials have many applications, as a penetrant liquid for crack detection, synthetic resins, plastics, printing inks, non-destructive testing and sports ball dyeing.

The aim value of this review is to define the scope and limitation of microwave synthesis procedures for the synthesis of novel fluorescent dyes via a simple and economic way.

To investigate the effect of poly ethylene glycol (PEG) chain length on the dielectric properties of paraffin‐based PEG polymers (H(CH₂)_n–(OCH₂CH₂)_mOH) from both experimental and analytical approach.

Dielectric constant studies of paraffin‐based PEG polymers were carried out at temperatures above the melting point. The measurements were carried out at frequencies between 0.4 and 20 GHz. The number of PEG units, m, was varied from 0 to 80 to investigate the effect of the PEG chain length on the dielectric properties of the whole polymer.

With the existence of a dipole moment on PEG but not on pure paraffin, both the real and imaginary part of the dielectric permittivity become larger with increasing chain length of PEG. PEG 3000 showed the highest dielectric constants in the measured frequency range. The effect of the PEG chain length can be explained well by introducing the fraction of molecular weight of PEG divided by the molecular weight of the whole polymer (we call this fraction “Mw fraction of PEG”). Both, real and imaginary part of the dielectric permittivity exhibit a cubic dependence of the molecular weight fraction, and the loss tangent exhibits a linear dependence. These relationships make it possible to predict the microwave heating of the polymer in function of the PEG chain length, carbon chain length and microwave frequency.

For the dielectric permittivity of paraffin‐based PEG polymers, the effect of the PEG chain length, carbon chain length and applied microwave frequency on the loss tangent was explained well by introducing the molecular weight fraction of PEG.

Although building information modelling (BIM) brings various benefits and open up the construction industry to many new possibilities, it is not without some challenges. Blockchain has the potential to resolve some of these problems. It has shown that blockchain and BIM can potentially work together in bringing various benefits to all project stakeholders. However, there is a lack of research and knowledge in relation to blockchain-based BIM. Therefore, the purpose of this study is to close this gap by looking into the potential functionality and workability of blockchain within a BIM environment.

A four-stage preferred reporting items for systematic reviews and meta-analyses systematic literature review technique has been used to review the blockchain- and BIM-related information sources published. A total of 53 journal articles, 13 books and 27 other resources including that of reports and websites have been included in this paper.

Blockchain-based BIM has countless possibilities, ranging from simple tasks such as tracking of orders to automation of construction payment claims. The literatures have suggested that the several weaknesses that BIM possesses including trust issue, asset ownership issue and data reliability issue could be resolved by incorporating blockchain into its processes.

Because of the lack of researches on the workability of blockchain and BIM, this paper aims to close this gap by proposing a framework for the interaction between blockchain and BIM for a typical building project. This paper has reviewed a substantial amount of currently available knowledge on blockchain-based BIM and its relevancy to the construction industry. This paper believes that the information could be of use to potential BIM tools maker and the construction industry for the betterment of BIM implementation throughout a project life cycle.

Environmental communication has been a profession and a subject of study for decades. Communication currently revolves around the anthropogenic ecological catastrophe, which makes the field’s early self-description as a crisis discipline even more pertinent. How communication is used and perceived significantly impacts how human-caused climate disasters and other environmental and social problems develop and how solutions are offered. The phenomenon of technology has shown significant impacts on how people refer to environmental communication. While bibliometric analysis (BA) helps understand the trends, ChatGPT can generate information related to environmental communication. How are they different from each other? What are the limitations? This study aims to identify the trends and limitations of BA and ChatGPT that are associated with environmental communication.

A qualitative approach is used, which refers to BA using the Biblioshiny software (n = 867) and content analysis on ChatGPT 3.5. It uses a systematic technique for keyword search, namely, environmental and communication, from 2000 to 2022.

There has been a decrease in the scientific production of studies starting in 2021 and 2022, which is believed to be due to the COVID-19 pandemic. ChatGPT provides valuable information but is rather complimentary to BA. ChatGPT is unable to provide statistical information related to environmental communication among Scopus-indexed publications.

This study focuses on the literature published in Scopus from 2000 to 2022. The keyword is limited to “environmental” and “communication.” Besides, the choice of keywords made it specific to the studies involved in the BA, which may not include some other studies if the keywords are not listed.

The originality of the research focuses on the field of environmental communication, its evolution within previous literature and the comparison between BA and the use of ChatGPT for understanding trends and limitations within this field. The text touches upon various aspects, such as the historical context of environmental communication, the impact of technology, the trends in scientific production among Scopus journal papers and the limitations of using ChatGPT compared to BA.