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Residential energy consumption forecasting has immense value in energy efficiency and sustainability. In the current work we tried to forecast energy consumption on residences in Athens, Greece. As a proof of concept, smart sensors were installed into two residences that recorded energy consumption, as well as indoors environmental variables (humidity and temperature). It should be noted that the data set was collected during the COVID-19 pandemic. Moreover, we integrated weather data from a public weather site. A dashboard was designed to facilitate monitoring of the sensors' data. We addressed various issues related to data quality and then we tried different models to forecast daily energy consumption. In particular, LSTM neural networks, ARIMA, SARIMA, SARIMAX and Facebook (FB) Prophet were tested. Overall SARIMA and FB Prophet had the best performance. Copyright © 2023 by SCITEPRESS - Science and Technology Publications, Lda. Under CC license (CC BY-NC-ND 4.0)
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The application of Industry 4.0 (I4.0) in the field of logistics leads to the emergence and development of the concept of logistics 4.0. Many I4.0 technologies have been applied in the field of logistics. The goal of this research is to analyze the applicability of nine key I4.0 technologies in logistics centers (LC). For this purpose, an integrated MEREC (MEthod based on the Removal Effects of Criteria)—fuzzy MARCOS (Measurement of Alternatives and Ranking according to COmpromise Solution) model was developed. The applicability of nine I4.0 technologies was evaluated based on 15 subcriteria within three main groups of criteria, namely, technological, social and political, and economic and operative. Using the MEREC method, the weight values of the criteria and subcriteria were determined, while the technologies were ranked using the fuzzy MARCOS method. Based on the results obtained by applying this integrated MCDM (multicriteria decision-making) model, CC was identified as the best alternative, i.e., the technology that is most applicable in logistics centers, followed by IoT and big data. An analysis of the sensitivity of the obtained results to the change in the importance of the criteria was carried out, which shows certain changes in the ranking when the importance of the most important criterion changes.
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The moisture levels in sausages that were stored for 16 days and added with different concentrations of orange extracts to a modification solution were assessed using response surface methodology (RSM). Among the 32 treatment matrixes, treatment 10 presented a higher moisture content than that of treatment 19. Spectral pre-treatments were employed to enhance the model's robustness. The raw and pre-processed spectral data, as well as moisture content, were fitted to a regression model. The RSM outcomes showed that the interactive effects of [soy lecithin concentration] × [soy oil concentration] and [soy oil concentration] × [orange extract addition] on moisture were significant (p < 0.05), resulting in an R2 value of 78.28% derived from a second-order polynomial model. Hesperidin was identified as the primary component of the orange extracts using high-performance liquid chromatography (HPLC). The PLSR model developed from reflectance data after normalization and 1st derivation pre-treatment showed a higher coefficient of determination in the calibration set (0.7157) than the untreated data (0.2602). Furthermore, the selection of nine key wavelengths (405, 445, 425, 455, 585, 630, 1000, 1075, and 1095 nm) could render the model simpler and allow for easy industrial applications.
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COVID-19 is a serious epidemic that not only endangers human health, but also wreaks havoc on the development of society. Recently, there has been research on using artificial intelligence (AI) techniques for COVID-19 detection. As AI has entered the era of big models, deep learning methods based on pre-trained models (PTMs) have become a focus of industrial applications. Federated learning (FL) enables the union of geographically isolated data, which can address the demands of big data for PTMs. However, the incompleteness of the healthcare system and the untrusted distribution of medical data make FL participants unreliable, and medical data also has strong privacy protection requirements. Our research aims to improve training efficiency and global model accuracy using PTMs for training in FL, reducing computation and communication. Meanwhile, we provide a secure aggregation rule using differential privacy and fully homomorphic encryption to achieve a privacy-preserving Byzantine robust federal learning scheme. In addition, we use blockchain to record the training process and we integrate a Byzantine fault tolerance consensus to further improve robustness. Finally, we conduct experiments on a publicly available dataset, and the experimental results show that our scheme is effective with privacy-preserving and robustness. The final trained models achieve better performance on the positive prediction and severe prediction tasks, with an accuracy of 85.00% and 85.06%, respectively. Thus, this indicates that our study is able to provide reliable results for COVID-19 detection.
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The 2nd Agrifood System International Conference (ASIC)Professor Jurnalis Kamil Convention Hall, Padang, West Sumatra, Indonesia, 8-9 November 2022"Research advancement and innovations in agroecology and smart agrifood systems.”The 2nd Agrifood System International Conference (ASIC 2022) was successfully held on 8-9 November 2022. Due to the covid-19 pandemic, this event was held virtually via the zoom platform, directly from Professor Jurnalis Kamil Convention Hall, Padang, West Sumatra, Indonesia. This event was organized by the Faculty of Agriculture, Universitas Andalas, Indonesia, and became a part of the event to commemorate the 68th anniversary of the faculty. The theme of the ASIC 2022 was: "Research advancement and innovations in agroecology and smart agrifood systems.”There have been numerous revolutions in agriculture, which have improved competency and led to record-breaking yields and gains. The latest process is "smart farming,” contributing to humanity's survival and future prosperity. Smart farming presents numerous prospects for pervasive interconnection and database computer technology as part of Industry 4.0. Smart farming is the idea of agricultural practice in a creative manner while utilizing cutting-edge technology to improve the quantity and quality of agricultural goods. New methods to assure global food safety are part of the future of the food manufacturing industry. It enables farmers to boost yields more effectively and efficiently. Fertilizers, labor, seeds, and water are just a few resources that can be saved. Smart farming has supporting applications, including land management, selection of varieties, minimizing synthetic fertilizers and pesticide inputs, and replacing them with environmentally friendly inputs. Research and related technological innovations have been carried out but have yet to be adopted and properly integrated.The main objective of this conference was to provide a venue for exchanging knowledge, scientific advancement, and innovative ideas among researchers, academicians, governments, and organizations. The scope includes plant breeding and crop production, soil management, plant protection and food safety, the socio-economic of agriculture and natural resources, and all topics related to agriculture. The committee received more than two hundred paper s coming from 46 institutions, national and international. We encourage student presenters from undergraduate to doctoral programs to present their papers;hence, around 25% of s come from them.The conference program was divided into two main segments: plenary and parallel. The plenary session invited 13 speakers from within and outside the country and was attended by 610 participants during the two days' activities. On behalf of the committee, we greatly appreciate the seven speakers contributing and sharing their knowledge at this event: Dr. Silvain R Perret, Scientific Director of CIRAD, France;Mr. Pierre Ferrand from FAO, Regional Office for Asia and the Pacific;Prof. Norman Uphoff, SRI Scientist from Cornell University, USA;Dr. Jauhar Ali, Rice hybrid breeder from IRRI, Philippines;Dr. Trevor A. Jackson, Plant protection scientist from IAPPS/ Coordinator Region XII;Prof. Shamshuddin Jusop, Soil Science Scientist from UPM, Malaysia;and Dr. Wahono: Drone creator from UMM, Indonesia. We also introduced five invited speakers from the Faculty of Agriculture: Dr. Irawati Chaniago - Crop Production;Dr. Dini Hervani - Plant Breeding;Dr. Eka Candra Lina - Plant Protection;Dr. Yuerlita - Socio-economics of Agriculture;Dr. Hery Bachrizal Tanjung - Agricultural Extension. In addition, we have provided an online workshop conducted as a side event on successfully publishing an article in IOP-EES Proceeding.Finally, let me express my sincere gratitude to all presenters, participants, and committee members who contributed significantly to this event's success. Special thanks go to the Rector of Universitas Andalas and the head of the research institute and community service of Universi as Andalas for all the support during the event. We hope to deliver the 3rd ASIC in 2024.Warmest regards,Dr. My SyahrawatiChairperson of the Organizing CommitteeList of Documentations, Conference Committee, Conference Schedule, Parallel Schedule, List of Presenters are available in this Pdf.
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The article examines the application of e-commerce systems and technologies that have a positive impact on the development of the economy of the post-coronavirus period and the formation of appropriate technical and technological infrastructure for it, as well as promising features and directions of e-commerce. The physical and virtual opportunities created by e-commerce technologies for buyers and sellers are explained. The advantages of e-commerce in the international economic space have been identified. The functions of e-business models in accordance with the commercial stages of enterprises are explained. It was noted that the development of ICT has accelerated the process of transition from traditional commerce to e-commerce, led to the emergence of new global trends in e-commerce. These innovations have raised the issue of the application of modern ICT in the development of e-commerce on the platform of the 4.0 Industrial Revolution. Taking into account these factors, the presented article discusses the application of modern technologies in e-commerce systems, such as 3D modeling, the Internet of Things, artificial intelligence, big data. Features of application and regulation mechanisms of E-commerce systems in real economic sectors, which have a direct stimulating effect on economic growth in Azerbaijan, have been studied. Recommendations were given for the modernization and use of e-commerce systems with the application of the latest ICT technologies.The purpose of the research. The main goal of the scientific research carried out in the article was to develop the scientific-methodological basis for the regulation of the application of e-commerce systems and the study of perspective development problems in the so-called post-coronavirus period after 2020. In the article, attention was paid to the problems of regulation of the application of e-commerce systems and the development of recommendations on increasing the efficiency of prospective development directions.Taking into account the characteristics of the relevant electronic business models, applying them in accordance with the commercial stages of the enterprises' activities and obtaining effective results were among the main goals. Attempts have been made to implement e-commerce systems based on the developing technologies of the Industry 4.0 platform. An attempt was made to solve the issue of using modern ICT in the development of trade processes, which corresponds to the 4.0 Industrial revolution platform. The main stages of application of modern technologies such as 3D modeling, the Internet of Things, artificial intelligence, and Big Data in electronic commerce systems are described.The following are included among the goals of the conducted scientific research: investigation of the application features and regulation mechanisms of e-commerce systems that have a stimulating effect on the economic development of Azerbaijan in real economic sectors, development of recommendations on increasing the efficiency of electronic commerce systems using modern ICT technologies, etc.Research methods used. In the post-coronavirus period, the following research methods were used in the study of the problems of regulation of the application of e-commerce systems and prospective development directions and in the development of their scientific and methodological bases: a systematic analysis, correlation, and regression analysis, mathematical and econometric modeling methods, expert evaluation method, measurement theory, algorithmization, ICT tools, and technologies, etc.Achievements of the author. Achievements of the author. In the so-called post-coronavirus period after 2020, a special approach was taken to the application of e-commerce systems and technologies, which have a positive impact on the development of the economy as an innovative element, and to the study of its prospective development features and directions. By providing scientific support to ensure the effective formation of the digital economy and its sustainability, the researcher offered relev nt recommendations to achieve the solution to some of the goals set before the country. It should be noted that the development of e-commerce systems based on technologies relevant to the Industry 4.0 platform can give a serious impetus to the development of the sustainability of the digital economy.Due to the fact that e-commerce technologies create new additional physical and virtual opportunities for buyers and sellers, the scientific-methodological approaches proposed by the author develop them as a special tool for ensuring the stability of both e-commerce systems and the digital economy in general. The proposals presented will lead to more effective results for the economy to be more cyber resilient through the application of e-commerce systems in the so-called post-coronavirus era. The researcher showed that the effective application of electronic business models in the activities of enterprises can help to achieve effective results. In the development of e-commerce, solutions to the issues of application of 4.0 Industrial technologies such as 3D modeling, Internet of Things, artificial intelligence, and Big Data can be considered as a contribution to the investigation of solutions to existing problems in economic development. For this reason, the means and mechanisms proposed by the author for solving the problems of regulation of the application of e-commerce systems in the post-coronavirus era can be considered one of the main ways to ensure the stability and development of the digital economy.
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The main purpose of our study is to form a demonstration model of the main processes for introducing digital technologies into the human resources management system for engineering enterprises. Digital transformations are associated with management changes, which are based on the technologies of the Internet of Things, artificial intelligence, blockchain, machine learning, Industry 4.0, Big Data in all spheres of public life. Investing in human capital has always been considered a productive investment. The digital economy has increased the urgency of increasing labor productivity through the transformation of human governance mechanisms. The main and key processes of the introduction of digital technologies in the human resources management system of the engineering enterprise were considered. The digitalization of society has radically changed people's lives and opened up new opportunities in the field of human resources management. The digital transformation of the human resources system affects all types of businesses, from large corporations to small micro-firms. As a result, the key stages and processes of implementation of digital technologies in the human resources management system of the enterprise were presented. The research methodology consisted of the application of modeling and graphical display methods.
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PurposeContactless shopping concepts meet the needs of those consumers who want to minimise social interactions, especially due to COVID-19;they also offer added value by combining the advantages of traditional shopping with digital features that stem from online shopping. The development of digitalised retail concepts has been made possible through digitisation and the use of new technologies. To date, the concepts have been created with various formats through the application of the most advanced Industry 4.0 technologies. This paper aims to provide a deepened understanding of the latest trends and draws attention to the various classes, including shopping functionalities and features.Design/methodology/approachThis paper performs a review of current disruptive and new business retail concepts within the grocery retail industry in Germany. Therefore, a secondary research methodology and observations were performed to create an overview and a categorization. This categorization has been used to identify the related cases.FindingsThe results add to the literature as follows. First, a matching of contactless shopping to innovative business models is made. Second, a status-quo analysis of contactless shopping solutions in Germany is carried out with defined set of criteria. This study created a list of all major available contactless shopping solutions. Third, this study examines two new business models, namely, automated vending machines and walk-in stores, which meet the changes in consumer behaviour and needs in times of the COVID-19 pandemic.Originality/valueThis paper provides a deeper understanding of the latest trends within the retail industry and draws attention to disruptive business models as well as the functionalities and features of shopping solutions. New store concepts launched during the COVID-19 pandemic have resulted in unique selling propositions of 24-h everyday shopping and contactless shopping.
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Fibre-reinforced plastic (FRP) materials are attracting growing interest because of their high specific mechanical properties. These characteristics, in addition to a high level of tailorability and design of freedom, make them attractive for marine, aerospace, automotive, sports and energy applications. However, the large use of this class of material dramatically increases the amount of waste that derives from end-of-life products and offcuts generated during the manufacturing processes. In this context, especially when thermosetting matrices are considered, the need to deeply study the recycling process of FRPs is an open topic both in academic and industrial research. This review aims to present the current state of the art of the most affirmed recycling technologies used for polymeric composites commonly used in industrial applications, such as carbon and glass FRPs. Each recycling method (i.e., chemical, thermal and mechanical) was analysed in terms of technological solutions and process parameters required for matrix dissolution and fibre recovery, showing their advantages, drawbacks, applications and properties of the recycled composites. Therefore, the aim of this review is to offer an extensive overview of the recycling process of polymeric composite materials, which is useful to academic and industrial researchers that work on this topic.
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The Metaverse allows the integration of physical and digital versions of users, processes, and environments where entities communicate, transact, and socialize. With the shift towards Extended Reality (XR) technologies, the Metaverse is envisioned to support a wide range of applicative verticals. It will support a seamless mix of physical and virtual worlds (realities) and, thus, will be a game changer for the Future Internet, built on the Semantic Web framework. The Metaverse will be ably assisted by the convergence of emerging wireless communication networks (such as Fifth-Generation and Beyond networks) or Sixth-Generation (6G) networks, Blockchain (BC), Web 3.0, Artificial Intelligence (AI), and Non-Fungible Tokens (NFTs). It has the potential for convergence in diverse industrial applications such as digital twins, telehealth care, connected vehicles, virtual education, social networks, and financial applications. Recent studies on the Metaverse have focused on explaining its key components, but a systematic study of the Metaverse in terms of industrial applications has not yet been performed. Owing to this gap, this survey presents the salient features and assistive Metaverse technologies. We discuss a high-level and generic Metaverse framework for modern industrial cyberspace and discuss the potential challenges and future directions of the Metaverse's realization. A case study on Metaverse-assisted Real Estate Management (REM) is presented, where the Metaverse governs a Buyer–Broker–Seller (BBS) architecture for land registrations. We discuss the performance evaluation of the current land registration ecosystem in terms of cost evaluation, trust probability, and mining cost on the BC network. The obtained results show the viability of the Metaverse in REM setups.
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The COVID-19 pandemic has had a massive impact on the global aviation industry. As a result, the airline industry has been forced to embrace new technologies and procedures in order to provide a more secure and bio-safe travel. Currently, the role of smart technology in airport systems has expanded significantly as a result of the contemporary Industry 4.0 context. The article presents a novel construction of an intelligent mobile robot system to guide passengers to take the plane at the departure terminals at busy airports. The robot provides instructions to the customer through the interaction between the robot and the customer utilizing voice communications. The usage of the Google Cloud Speech-to-Text API combined with technical machine learning to analyze and understand the customer's requirements are deployed. In addition, we use a face detection technique based on Multi-task Cascaded Convolutional Networks (MTCNN) to predict the distance between the robot and passengers to perform the function. The robot can guide passengers to desired areas in the terminal. The results and evaluation of the implementation process are also mentioned in the article and show promise.
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PurposeThe authors observe the influence of intellectual capital (IC) on innovation performance with the mediating role of interorganizational learning (IOL) in the Pakistani automotive industry. Besides, industrial Internet of things (IoT) technology is used as moderating variables between IOL and innovation performance.Design/methodology/approachStructural equation modeling (SEM) presents scholars with extra flexibility and enhanced research conclusions. SEM is described as a statistical methodology and the best tool used for hypothesis testing. The authors used partial least squares SEM for testing hypotheses. The simple random sampling technique followed to collect data from respondents, and 492 questionnaires were used for analysis.FindingsThe outcomes reveal that IC enhances innovation performance and IOL. Moreover, IOL increases innovation performance. IOL significantly mediates between IC and innovation performance. Industrial IoT technology improves innovation performance. Finally, industrial IoT technology strengthens the positive association between IOL and innovation performance.Practical implicationsThis study concentrates on the issue of how managers use IOL and industrial IoT technology to take higher advantage of IC that increases innovation performance.Originality/valueThis is the initial study that builds a theoretical framework to integrate IC, IOL, industrial IoT technology and innovation performance. Although prior researchers observe the association between IC and innovation performance, less concentration was paid to understand the role of interorganizational leadership and industrial IoT technology in leveraging organizational IC.
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• PrefaceIt is our privilege to present the proceedings of the two-day online Conference entitled "International Conference on Advanced Earth Sciences and Foundation Engineering (ICASF-2022)”.The Conference was held virtually considering COVID–19 pandemics, ensuing gathering, and travel restrictions in the nation and worldwide. Yet, despite the issues, the virtual ICASF-2022 took place on 23rd and 24thJune 2022 and attracted a more significant number and diverse mix of attendees than it would have done as per expectations. The Organizers, i.e., ChandigarhUniversity, Mohali, India, which runs the event, seek to promote international collaborations in Research and Innovation. The Conference was delivered through ZOOM Cloud Meeting technology. More than 200 extra individuals signed upto ICASF-2022 over the guests, presenters, and invited attendees because of easier online access. Collectively more than 450 people attended from 15 countries. The Conference had delegates, participants, and attendees from Tanzania, South Africa, Kazakhstan, Russia, Afghanistan, Bangladesh, Bhutan, Nepal, and European countries some of whom might not otherwise have come because of the distance and time constraints in traveling. The Conference consists of six sessions, including inaugural and valedictory. Prof. (Dr.) Mikhael Bechelany from CNRS, France, Trinidad graced the plenary session along with Prof. (Dr.) Luminita Andronic, Professor at the Product Design and Environment Faculty, Transilvania University of Brasov, Romania, Prof. (Dr.) Valeria De Matteis, Professor at the Department of Mathematics and Physics "Ennio De Giorgi” of the University of Salento, Lecce (Italy), and Prof. (Dr.) Siraj Muhammed Pandhiani, Professor in the Department of General Studies, Jubail University College, Saudi Arabia. Furthermore, Four Keynote addresses were given by researchers and scientists from NIT, Kurukshetra, GHRCEM, Pune, National Agri-Food Biotechnology Institute, Mohali, Punjab, Chaudhary Charan Singh Haryana Agriculture University, Haryana. Overall, 130 paper presentations were delivered by authors in four conference technical sessions. Authors were facilitated with 15 minutes to present their papers, followed by 5 minutes of discussion and query session. The paper presentation and discussion emphasized incorporating Advanced Earth Science and Foundation Engineering, and compatibility withconstruction. The national and international research scenario on Advanced Earth Science and Foundation Engineering seeks to reduce negative impacts on the ecosystem, modern era development, and Future possibilities for sustainability. Thereby role play in Sustainable Development Goals. The primary objectives of today's development are reducing the consumption of non-renewable resources, minimizing waste, and creating a healthy environment. Consequently, interdisciplinary and integrated innovations have resulted in numerous smart solutions. This event provided a forum for researchers from different scientific and engineering fields to deliberate and collaborate at national and international levels for translating research into intelligent possibilities to make human life better.Chandigarh University, Gharuan, the leading university in research and Innovation in India, sponsored this Conference. This Conference provided an opportunity for in-depth technical discussions and the exchange of innovative ideas on a wide range of possibilities to explore the potential of their applications in industry and society. Moreover, young researchers were exposed to emerging trends and research areas that have significant technical and scientific importance for sustainable development.List of Conference photographs, Sponsoror funding acknowledgements, committees/participants are available in this Pdf.
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The International Conference on Synchrotron Radiation Instrumentation (SRI) is a unique and significant international forum held every three years in the community of synchrotron radiation (SR) and free electron lasers (FEL). It is the prime forum for fostering connections between cutting-edge synchrotron radiation instrumentation, science, and the requirements of the user community. The SRI 2021 had originally been scheduled to take place in Hamburg in summer 2021. Due to the COVID-19 pandemic, it was postponed to 2022 and held as an online event.More than 1160 international participants from 25 countries met virtually at the SRI 2021. In nearly 290 talks and 450 posters, latest results were presented. Although it was an online-only conference, lively discussions took place in the nearly 40 parallel sessions, and the eight poster sessions were also very well attended.The main topics of the SRI conference were: new SR and FEL facilities, update plans of these facilities, and recent developments in various instrumentation areas like beamline design, X-ray optics, sample environments, detectors and spectrometers, data acquisition, and data analysis techniques or automation. These innovations contributed to new results for a wide range of experimental techniques and scientific applications such as X-ray scattering and spectroscopy, bio- and scanning imaging, structural biology crystallography, coherent techniques, or in-situ/operando methods. A dedicated session concerned industrial applications of synchrotron radiation.The field of synchrotron radiation instrumentation is currently seeing very active development due to various factors. Firstly, the number of SR sources world-wide is increasing significantly, with new sources in particular in Europe and in Asia. Secondly, a new generation of storage rings with new multi-bend achromat lattices are being implemented at a growing number of existing facilities. These facilities offer a significant increase of brilliance and coherence and thereby lead to new and improved applications of synchrotron radiation, in particular in the areas of imaging and high spatial resolution. Thirdly, the increase of soft and hard X-ray FEL sources worldwide and the maturation of their experimental techniques and scientific applications is the background for a strongly increasing number of developments for ultrafast time-resolved investigations of dynamic behaviour of materials and reactions. Most of the keynote speakers and many invited and contributed talks or posters at the conference showed new results directly related to these three major developments.Lists of International Advisory Committee (listed by facility), Scientific Programme Committee (listed by facility), Local Organising Committee (listed by facility) are available in this PDF.
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The proceedings provide a selection of thirty-eight peer-reviewed papers presented at the 11th Global Conference on Materials Science and Engineering (CMSE 2022), held as a virtual conference on September 16-19, 2022.By the tradition annually followed in the full decade of its history, CMSE 2022 was dedicated to various aspects of Materials Science and Engineering. Given the aggravated Covid situation, the conference format was fully converted to the online mode to ensure the safety of participants, abandoning the previously scheduled on-site preparation plans in Shenzhen, China.CMSE 2022 was conducted via Microsoft Teams. The full three days of the conference comprised namely keynote speeches, oral presentations, and poster presentations, each part followed by a Q&A discussion. Firstly, the conference audience containing over a hundred participants from 23 countries enjoyed the keynote speeches of three distinguished professors: Prof. Qixin Guo from Saga University, Japan, Prof. Yarub Al-Douri from the American University of Iraq, Iraq, and Prof. Rodrigo Martins from Universidade Nova de Lisboa, Portugal, who shared their deep insights on rare earth doped semiconductors, quinternary alloys’ multi-application, and green and low-cost printed electronics, respectively. Next, over eighty oral and poster presentations were delivered successfully with informative results from related materials science and engineering fields. More detail can be found in the online version of the conference program. The online format of the conference somewhat limited the informal discussion opportunities for its participants. However, despite Covid-induced restrictions, this conference fulfilled its ultimate goal of bringing together experts from universities, academic institutions, industrial companies, and so on, updating the state-of-the-art developments and challenges.The selected thirty-eight contributions cover the latest advances in innovative materials, materials technology and materials properties, microstructure, testing & characterization, processing, etc. They focus on theoretical and analytical methods, numerical simulations, and experimental techniques with regard to industrial applications. All papers passed a rigorous reviewing process by the International Committee experts, whose reviews and comments were crucial for enhancing the scientific merit and quality of the proceedings.List of Committee Members is available in this Pdf.
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In the spirit of innovation, the development of an intelligent robot system incorporating the basic principles of Industry 4.0 was one of the objectives of this study. With this aim, an experimental application of an industrial robot unit in its own isolated environment was carried out using neural networks. In this paper, we describe one possible application of deep learning in an Industry 4.0 environment for robotic units. The image datasets required for learning were generated using data synthesis. There are significant benefits to the incorporation of this technology, as old machines can be smartened and made more efficient without additional costs. As an area of application, we present the preparation of a robot unit which at the time it was originally produced and commissioned was not capable of using machine learning technology for object-detection purposes. The results for different scenarios are presented and an overview of similar research topics on neural networks is provided. A method for synthetizing datasets of any size is described in detail. Specifically, the working domain of a given robot unit, a possible solution to compatibility issues and the learning of neural networks from 3D CAD models with rendered images will be discussed.
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Predictive maintenance plays an important role in managing commercial buildings. This article provides a systematic review of the literature on predictive maintenance applications of chilled water systems that are in line with Industry 4.0/Quality 4.0. The review is based on answering two research questions about understanding the mechanism of identifying the system’s faults during its operation and exploring the methods that were used to predict these faults. The research gaps are explained in this article and are related to three parts, which are faults description and handling, data collection and frequency, and the coverage of the proposed maintenance programs. This article suggests performing a mixed method study to try to fill in the aforementioned gaps.
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The depletion of petroleum-based resources and the adverse environmental problems, such as pollution, have stimulated considerable interest in the development of environmentally sustainable materials, which are composed of natural fiber-reinforced polymer composites. These materials could be tailored for a broad range of sustainable industrial applications with new surface functionalities. However, there are several challenges and drawbacks, such as composites processing production and fiber/matrix adhesion, that need to be addressed and overcome. This review could provide an overview of the technological challenges, processing techniques, characterization, properties, and potential applications of NFRPC for sustainable industrial applications. Interestingly, a roadmap for NFRPC to move into Industry 4.0 was highlighted in this review.
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Meat 4.0 refers to the application the fourth industrial revolution (Industry 4.0) technologies in the meat sector. Industry 4.0 components, such as robotics, Internet of Things, Big Data, augmented reality, cybersecurity, and blockchain, have recently transformed many industrial and manufacturing sectors, including agri-food sectors, such as the meat industry. The need for digitalised and automated solutions throughout the whole food supply chain has increased remarkably during the COVID-19 pandemic. This review will introduce the concept of Meat 4.0, highlight its main enablers, and provide an updated overview of recent developments and applications of Industry 4.0 innovations and advanced techniques in digital transformation and process automation of the meat industry. A particular focus will be put on the role of Meat 4.0 enablers in meat processing, preservation and analyses of quality, safety and authenticity. Our literature review shows that Industry 4.0 has significant potential to improve the way meat is processed, preserved, and analysed, reduce food waste and loss, develop safe meat products of high quality, and prevent meat fraud. Despite the current challenges, growing literature shows that the meat sector can be highly automated using smart technologies, such as robots and smart sensors based on spectroscopy and imaging technology.