Role-Based data visualization for Industrial IoT

The competition among manufacturers in the global markets calls for the enhancement of the agility and performance of the production process and the quality of products. As a result, the production systems should be designed in a way to provide decision-makers with visibility and analytics. To fulfill these objectives, the development of factory information systems in manufacturing industries has been introduced as a practical solution in the past few years. On the other hand, the volume of data generated on the factory floor is rising. To improve the efficiency of manufacturing process, this amount of data should be analyzed by decision-makers. To cope with this challenge, visualization assists decision-makers to gain insight into data. To give a better perspective of collected data to decision-makers, effective visualization techniques should be employed. Adequate data visualization allows the end user to have better understanding of data and make effective decisions faster. Meanwhile, the adoption of the Service-Oriented Architecture (SOA) and Internet of Things (IoT) as state-of-the-art technologies are among the most prominent trends in industrial automation. IoT technology is expected to generate and collect data from various sensors and devices within the production system, and enables enterprises to have real-time visibility into the flow of production process. Moreover, data received from factory floor should be transmitted from back-end side to the front-end side for future analysis. To implement the exchange of data efficiently, the solution should support different communication protocols to make interoperability among heterogeneous devices on shop floor. This study describes an approach for building a role-based visualization of industrial IoT. An extensible architecture was provided by which the future growth of data and emerging new protocols has been anticipated. By using the IoT platform introduced in this thesis, selected KPIs can be monitored by different levels of enterprise. Three prototype IoT dashboards have been implemented for a pilot production line, “Festo didactic training line” located in Seinäjoki University of Applied Sciences (SeAMK) and results have been validated

The COVID-19 pandemic and healthcare utilization in Iran: evidence from an interrupted time series analysis

Objectives This study aimed to examine the effect of the coronavirus disease 2019 (COVID-19) outbreak on the hospitalization rate, emergency department (ED) visits, and outpatient clinic visits in western Iran. Methods We collected data on the monthly hospitalization rate, rate of patients referred to the ED, and rate of patients referred to outpatient clinics for a period of 40 months (23 months before and 17 months after the COVID-19 outbreak in Iran) from all 7 public hospitals in the city of Kermanshah. An interrupted time series analysis was conducted to examine the impact of COVID-19 on the outcome variables in this study. Results A statistically significant decrease of 38.11 hospitalizations per 10,000 population (95% confidence interval [CI], 24.93–51.29) was observed in the first month of the COVID-19 outbreak. The corresponding reductions in ED visits and outpatient visits per 10,000 population were 191.65 (95% CI, 166.63–216.66) and 168.57 (95% CI, 126.41–210.73), respectively. After the initial reduction, significant monthly increases in the hospitalization rate (an increase of 1.81 per 10,000 population), ED visits (an increase of 2.16 per 10,000 population), and outpatient clinic visits (an increase of 5.77 per 10,000 population) were observed during the COVID-19 pandemic. Conclusion Our study showed that the utilization of outpatient and inpatient services in hospitals and clinics significantly declined after the COVID-19 outbreak, and use of these services did not return to pre-outbreak levels as of June 2021

A knowledge-based approach to the IoT-driven data integration of enterprises

Internet of Things (IoT) as a state-of-the-art technology has introduced businesses to new possibilities, thus allowing them to increase the efficiency and productivity of operational processes. Furthermore, the experiences gained by the employees of an organization can be shared among multiple corporations to facilitate the educational processes for employees through establishing learning environments within their businesses. In this study, we discuss the opportunities that IoT offers to businesses to integrate and share the massive amount of data generated by learning factories in enterprises as well as ongoing challenges in this domain. We further present the design and implementation of an ontology-based architecture for the development of IoT solution facilitating the collaborative business-to-business (B2B) knowledge sharing among enterprises to be used in their learning factory environments for educational matters. The proposed solution in this paper allows organizations to pursue their didactic purposes through the creation of an effective learning environment.publishedVersionPeer reviewe

Antibacterial activity of Avicennia marina leaves extract on Staphylococcus aureus, Escherichia coli and Pseudomonas aeruginosa

Background: Antibiotic resistance is one of the most common problems in medicine. Therefore discovering of new antibacterial components with least side effect is necessary. Based on the presence of biologically active constituents in Avicennia marina and its uses in alternative medicine, it is supposed that this plant has antibacterial effect. Methods: This study was designed as an "in vitro" study. In extraction procedure, 20% glycerin solution was utilized as solvent. In the screening step, S. aureus (ATCC 25923), E. coli (ATCC 25922) and P. aeruginosa (ATCC 27853) were exposed to extract with 90 mg/ml in concentration, separately. Thereafter, these three strains were examined with different concentrations of the extract to determine minimal bactericidal concentration (MBC). Also the effect of MBC was tested at time zero and after incubation time ranging from 2 to 24 hours. Results: The MBCs on S. aureus, E. coli and P. aeruginosa were 7.9, 33.8 and 15.8 mg/ml, respectively. The minimum times necessary for effectiveness of extract were as follows: 24h for S. aureus, 8h for E. coli and 12h for P. aeruginosa. Conclusion: Avicennia marina leaves extract has a significant antibacterial effect on E. coli and P. aeruginosa as gram negative bacteria, and S. aureus as a gram positive bacterium

Ultrasonographic evaluation of the thyroid gland and goiter prevalence in Bushehr port as an iodine- sufficient area: 6- year prospective study in schoolchild

Background: The determination of goiter prevalence in children by thyroid ultrasound is an important tool for assessing iodine deficiency disorders. The main aim of this study was to determine thyroid volume and goiter prevalence in schoolchildren of Bushehr port, based on 2007 normative values. Materials and Methods : A probability proportionate-to-size cluster sampling method was used to obtain a representative sample of 1148 school children of Bushehr port aged 7-10 years. The median and 97th percentile of thyroid volumes for age and body surface area (BSA) was measured by data of ultrasonography. The normative value of thyroid volume of the 2007 study was used as reference. Results: The 97th percentile of thyroid volume based on age or BSA in school children was higher than the international normative reference. The age-, and BSA-adjusted mean of thyroid volume was higher in both sexes than the thyroid volume of school children in the 2007 study (p<0.0001). Application of the native thyroid volume reference resulted in a goiter prevalence of 7.57%. Conclusion The thyroid volumes of schoolchildren and goiter prevalence in Bushehr port were generally high compared to the baseline data obtained 6 years ago. The environmental goiterogenic factors should be investigated in this iodine-sufficient area