ABSTRACT
Anthropogenic activities are among major contributors to the deterioration of coastal environmental quality. Reduction of these activities could improve the status. Hence, this study was carried out to investigate temporal variations of water quality parameters of Lukut and Port Dickson coastal waters during the first year of the COVID-19 pandemic. Three sampling events were carried out between February to March 2020 (Before COVID-19 pandemic movement control order - MCO), followed by September 2020 and from March to April 2021 (After one year of the first MCO). The parameters monitored were oil and grease (OG), nitrate (NO3-N), ammoniacal nitrogen (NH3-N), unionized ammonia (NH3), phosphate (PO4-P), and fecal coliform (Escherichia coli). The OG content was reduced to more than 99%, followed by ammonia, E. coli, ammoniacal nitrogen, and nitrates which decreased by 94.65%, 91.87%, 83.64%, and 80.58%, respectively, in the third sampling. Phosphate was the only element found to increase at specific sites during the third sampling, and this was expected to be influenced by other water parameters. The improvement of water quality, especially OG, ammonia, ammoniacal nitrogen, nitrates, and E. coli concentrations in the study area, was related to the restrictive human movement associated with the COVID-19 pandemic. © 2023 Author(s).
ABSTRACT
Recently, smart medical devices have become preva-lent in remote monitoring of patients and the delivery of medication. The ongoing Covid-19 pandemic situation has boosted the upward trend of the popularity of smart medical devices in the healthcare system. Simultaneously, different device manufacturers and technologies compete for a share in a smart medical device's market, which forces the integration of diverse smart medical de-vices into a common healthcare ecosystem. Hence, modern unified healthcare communication systems (UHCSs) combine ISO/IEEE 11073 and Health Level Seven (HL7) communication standards to support smart medical devices' interoperability and their communication with healthcare providers. Despite their advantages in supporting various smart medical devices and communication technologies, these standards do not provide any security and suffer from vulnerabilities. Existing studies provide stand-alone security solutions to components of UHCSs and do not cover UHCSs holistically. In this paper, we perform a systematic threat analysis of UHCSs that relies on attack-defense tree (ADTree) formalisms. Considering the attack landscape and defense ecosys-tem, we build an ADTree for UHCSs and convert the ADTree to stochastic timed automata (STA) to perform quantitative analysis. Our analysis using UPPAAL SMC shows that the Man-in-the-Middle and unauthorized remote access attacks are the most probable attacks that a malicious entity could pursue, causing mistreatment to patients. We also extract valuable information about the top threats, the likelihood of performing different individual and simultaneous attacks, and the expected cost for attackers. © 2022 IEEE.
ABSTRACT
BACKGROUND: SARS-CoV-2 was declared a global pandemic by the World Health Organization in March 2020. Vaccination is an important step to prevent COVID-19. AIM: This study aimed to analyze the predictive factors of community engagement in COVID-19 vaccination in East Java, Indonesia. METHODS: A cross-sectional study using purposive sampling was conducted on people aged 12–>60 years (n = 1,024) in Lamongan Regency, East Java Province, Indonesia, in August–September 2021. The data were collected using a self-administered questionnaire. Logistic regression analysis was used to estimate the relationship between community engagement in COVID-19 vaccination and other predictors. RESULTS: We included 1024 people aged 12–65 years, with a mean age (±SD) of 29 (12.7). Around 94.0% of the participants reported that they had been vaccinated twice. The role of supportive health cadres could increase community participation by 0.496 times in COVID-19 vaccination compared to the less supportive health cadres (OR = 0.496;95.0% CI: 0.292–0.845;p = 0.010). In addition, the role of supportive community leaders could increase community participation by 1.959 times in COVID-19 vaccination compared to the less supportive community leaders (OR = 1.959;95.0% CI: 1.080–3.551;p = 0.027). CONCLUSIONS: The role of health cadres and community leaders can increase community participation in COVID-19 vaccination. The partnership between community health center and community engagement in the COVID-19 vaccination program needs to be continued.
ABSTRACT
As societies rely increasingly on computers for critical functions, the importance of cybersecurity becomes ever more paramount. Even in recent months there have been attacks that halted oil production, disrupted online learning at the height of COVID, and put medical records at risk at prominent hospitals. This constant threat of privacy leaks and infrastructure disruption has led to an increase in the adoption of artificial intelligence (AI) techniques, mainly machine learning (ML), in state-of-the-art cybersecurity approaches. Oftentimes, these techniques are borrowed from other disciplines without context and devoid of the depth of understanding as to why such techniques are best suited to solve the problem at hand. This is largely due to the fact that in many ways cybersecurity curricula have failed to keep up with advances in cybersecurity research and integrating AI and ML into cybersecurity curricula is extremely difficult. To address this gap, we propose a new methodology to integrate AI and ML techniques into cybersecurity education curricula. Our methodology consists of four components: i) Analysis of Literature which aims to understand the prevalence of AI and ML in cybersecurity research, ii) Analysis of Cybersecurity Curriculum that intends to determine the materials already present in the curriculum and the possible intersection points in the curricula for the new AI material, iii) Design of Adaptable Modules that aims to design highly adaptable modules that can be directly used by cybersecurity educators where new AI material can naturally supplement/substitute for concepts or material already present in the cybersecurity curriculum, and iv) Curriculum Level Evaluation that aims to evaluate the effectiveness of the proposed methodology from both student and instructor perspectives. In this paper, we focus on the first component of our methodology - Analysis of Literature and systematically analyze over 5000 papers that were published in the top cybersecurity conferences during the last five years. Our results clearly indicate that more than 78% of the cybersecurity papers mention AI terminology. To determine the prevalence of the use of AI, we randomly selected 300 papers and performed a thorough analysis. Our results show that more than 19% of the papers implement ML techniques. These findings suggest that AI and ML techniques should be considered for future integration into cybersecurity curriculum to better align with advancements in the field. © American Society for Engineering Education, 2022
ABSTRACT
The COVID-19 pandemic has become a planetary concern that affecting the sustenance of the human population all around the globe. The effective measured has been taken in Malaysia to control the virus transmission by limiting the human vitality which unsurprisingly propitious to the environment. A monitoring study was conducted to assess the water quality status of surface seawater along the Port Dickson coast based on the Malaysian Marine Water Quality Index (MMWQI) and Malaysian Marine Water Quality Standards (MMWQCS) with an interval period of a year (March 2020-March 2021). In situ, water quality parameters incorporate temperature, pH, salinity, conductivity, dissolved oxygen (DO), and total dissolved solids (TDS) were measured at 14 sampling sites to evaluate the biochemical characteristics of water. Surface water samples were collected from the same sites and transported back to Universiti Putra Malaysia for nitrate (NO3-), ammonia (NH3), phosphate (PO4), biochemical oxygen demands (BOD), fecal coliform (Escherichia coli), and total suspended solids (TSS) analyses. The MMWQI showed the status of surface water from the Port Dickson coast was classified as moderate quality (50.41 - 64.05) for both sampling events. However, there are some indexes that showed significant decreases (p< 0.05) in the latter year. The concentration of nutrient pollution such as phosphate, nitrates, ammonia, fecal coliform as well as oil and grease, was decreased by 11.12%, 77.39%, 82.4%, 90.26%, and 99.9% respectively. The water parameters namely TDS, pH, and BOD levels were significantly decreased by 1.77%, 20.73%, and 77.16%. Certain parameters listed in the MMWQS such as temperature, pH, ammonia, fecal coliform, oil and grease were classified as Class 1 in March 2021. These occurrences recorded were greatly influenced by the reduction of the substantial human activities around the recreational beach of Port Dickson followed by the declaration of Movement Control Order (MCO) in Malaysia.
ABSTRACT
The restriction of daily and economic-related activities due to COVID-19 pandemic via lockdown order has been reported to improve air quality. This study evaluated temporal and spatial variations of four major air pollutant concentrations across Malaysia before (March 4, 2020–March 17, 2020) and during the implementation of different phases of Movement Control Order (MCO) (March 18, 2020–May 12, 2020) from 65 official regulatory air quality stations. Results showed that restriction in daily and economic activities has remarkably reduced the air quality in all sub-urban, urban, and industrial settings with relatively small contributions from meteorological conditions. Overall, compared to before MCO, average concentrations of PM2.5, CO, and NO2 reduced by 23.1%, 21.74%, and 54.0%, respectively, while that of SO2 was constant. The highest reduction of PM2.5, CO, and NO2 were observed in stations located in urban setting, where 63% stations showed significant reduction (p <0.05) for PM2.5 and CO, while all stations showed significant reduction in NO2 concentrations. It was also revealed that 70.5% stations recorded lower concentrations of PM2.5 during MCO compared to before MCO, despite that high numbers of local hotspots were observed simultaneously from NASA’s Moderate Resolution Imaging Spectroradiometer (MODIS). Spatial analysis showed that the northern part of Peninsular had the highest significant reduction of PM2.5, while the highest of NO2 and CO reduction were found in stations located in the central region. All pollutants exhibit similar diurnal trends when compared between pre-and during MCO although significant lower readings were observed during MCO. This study gives confidence to regulatory body;the enforcement of strict air pollution prevention and control policies could help in reducing pollution. © 2020, AAGR Aerosol and Air Quality Research. All rights reserved.