Context: People who have recently recovered from the threat of deteriorating coronavirus disease-2019 (COVID-19) have antibodies to the coronavirus circulating in their blood. Thus, the transfusion of these antibodies to deteriorating patients could theoretically help boost their immune system. Biologically, two challenges need to be surmounted to allow convalescent plasma (CP) transfusion to rescue the most severe COVID-19 patients. First, convalescent subjects must meet donor selection plasma criteria and comply with national health requirements and known standard routine procedures. Second, multi-criteria decision-making (MCDM) problems should be considered in the selection of the most suitable CP and the prioritisation of patients with COVID-19. Objective: This paper presents a rescue framework for the transfusion of the best CP to the most critical patients with COVID-19 on the basis of biological requirements by using machine learning and novel MCDM methods.

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Water quality monitoring plays a significant part in the transition towards intelligent and smart agriculture and provides an easy transition to automated monitoring of crucial components of human daily needs as new technologies are continuously developed and adopted in agricultural and human daily life (water). For the monitoring and management of water quality, this effort, however, requires reliable models with accurate and thorough datasets. Analyzing water quality monitoring models by utilizing sensors that gather water properties during live experiments is possible due to the necessity for precision in modeling. To convey numerous conclusions regarding the concerns, issues, difficulties, and research gaps that have existed throughout the past five years (2018–2022), this review article thoroughly examines the water quality literature. To find trustworthy peer-reviewed publications, several digital databases were searched and examined, including IEEE Xplore®, ScienceDirect, Scopus, and Web of Science. Only 50 articles out of the 946 papers obtained, were used in the study of the water quality monitoring research area. There are more rules for article inclusion in the second stage of the filtration process. Utilizing a real-time data acquisition system, the criteria for inclusion for the second phase of filtration looked at the implementation of water quality monitoring and characterization procedures. Reviews and experimental studies comprised most of the articles, which were divided into three categories. To organize the literature into articles with similar types of experimental conditions, a taxonomy of the three literature was created. Topics for recommendations are also provided to facilitate and speed up the pace of advancement in this field of study. By conducting a thorough analysis of the earlier suggested methodologies, research gaps are made clear. The investigation largely pointed out the problems in the accuracy of the models, the development of data-gathering systems, and the types of data used in the proposed frameworks. Finally, by examining critical topics required for the development of this research area, research directions toward smart water quality are presented.

In industrial manufacturing, wireless network can be used in supply chain, retail stock management, electronic security keys, and theft prevention. A proactive and cost effective solution advancement is needed in the industrial manufacturing to monitor and control output performance at a manufacturing plant. It is with this reason that the manufacturers require an efficient communication and real time feedback to maximize uptime and improve productivity. Consistent with the future market of new technologies deployment this invention proposes a new complete solution method and architecture of embedded active radio frequency identification with counter system through wireless mesh sensor network platform and smart data processing adopted through web-based monitoring system for industrial automation. The ability of the developed system to function in machine-to-machine wireless communication and the adoption of web-based monitoring and data centralization contributes improvement in reducing errors with human intervention. In this paper we discuss the framework approach of a smart web-based monitoring and data acquisition system on wireless mesh sensor network platform. The evaluations and measurements have been conducted in real world environments which are conducted at selected industrial production factory.

Technological devices are commonly used in different styles and for several uses with educational systems. Instructors have to avoid using technology together with the utmost effectiveness but to additionally serve as role models for pupils in regards to the correct use of technology. Different methods, strategies, equipment, along with tools are used to enhance the effectiveness of coaching and learning operations in the classroom, of that Digital Storytelling is among them. Digital Storytelling (DST) has transformed into a good educational tool for both students and teachers. This paper offers a review of DST as well as portrays where it originated from, how it really well may be utilized to help guide as well as how understudies that discover the way to whip their own advanced stories improve a lot of instruction abilities. What's more often, info is shown about the device which might be utilized to help the instructive utilization of DST. This paper, in addition, has a discussion on the usefulness of DST as being an instructional media program employed in the education process. The goal of this paper is to present the main components of DST used by specialists in DST concepts. This study also discussed the overview of DST combined with the learning atmosphere, particulars specific DST modals and determined the essential elements of DST from several experts to be able to centralize them to cultivate the framework with support different ICT technology. Moreover, the paper covers the justification for the selection of past studies related to main important elements of DST.