International Journal of Advances in Scientific Research and Engineering (IJASRE), ISSN:2454-8006, DOI: 10.31695/IJASRE
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The Effect of Training Adults on the Safe Use of Computers: An Awareness Campaign Initiative
Get PDFPeople across different age groups worldwide use computers and smart devices with access to the Internet. This highlights the importance of educating users and making them aware of the threats to cybersecurity, hazards of the Internet, privacy and safety of personal information, and various kinds of online attacks. This study investigates the level of awareness among adults of the safe use of computers with Internet access. Data were collected by using two surveys: An initial survey was conducted to measure the users’ level of awareness before they attended a lecture, training, or workshop. A follow-up survey was subsequently conducted after the lecture/training/workshop to measure its effects on the users' awareness and understanding of the safety and security of using devices connected to the Internet. We also investigate new methods to reduce cyberattacks, and the responsiveness of users to unknown links and threats.
The findings of this study indicates that there is a positive influence on the participants after the workshop as it improves their knowledge of the privacy and security issues related to the use of social media and the use of different internet tools and increase their awareness level about the cybercrimes and different threats in the digital world. Yet, the results still show struggles in understanding the safety of their personal information and their contents in social media. Hence, a recommendation of more training in the field of applying practical privacy and security steps is still required to enhance their skills and ability to protect themselves and educate others in their communities
Super-tokens Auto-encoders for image compression and reconstruction in IoT applications
Get PDFNew telecommunications networks are enabling powerful AI applications for smart cities and transport. These applications require real-time processing of large amounts of media data. Sending data to the cloud for processing is very difficult due to latency and energy constraints. Lossy compression can help, but traditional codecs may not provide enough quality or be efficient enough for resource-constrained devices. This paper proposes a new image compression and processing approach based on variational auto-encoders (VAEs). This VAE-based method aims to efficiently compress images while still allowing for high-quality reconstruction and object detection tasks. The encoder is designed to be lightweight and suitable for devices with limited computing power. The decoder is more complex and uses multi-level vector quantization to reconstruct high-resolution images. This approach allows for a simple encoder on edge devices and a powerful decoder on cloud servers. Key contributions include a low-complexity encoder, a new VAE model based on vector quantization, and a framework for using VAEs in IoT. The first experiments on reconstructed images on CelebA and ImageNet100 datasets show promising results in terms of MS-SSIM, PSNR, MSE and rFID compared to the literature and the ability of our approach to be used in IoT applications. Our approach presents results similar to complex algorithms like compression algorithms BPG in term of trade-off rate-distortion, and hierarchical auto-encoder (HQA) in terms of image reconstruction quality
Blockchain-Enabled MRO: Enhancing Transparency and Efficiency in Aircraft Maintenance
Get PDFBlockchain technology is emerging as a transformative solution for addressing challenges in aviation Maintenance, Repair, and Overhaul (MRO), particularly in enhancing transparency, efficiency, and data security. This study explores the integration of blockchain within MRO operations in the Philippine aviation industry, aiming to assess its impact on data management, part authentication, and regulatory compliance. Utilizing a mixed-methods approach, data were collected through surveys, interviews, and document analysis involving MRO professionals, blockchain experts, and industry stakeholders. Findings indicate that blockchain can significantly improve record transparency, reduce counterfeit risks, and streamline verification processes, leading to more efficient maintenance cycles. Blockchain’s decentralized, tamper-proof ledger system was noted to address inefficiencies in data reconciliation and enhance traceability, which are critical for regulatory compliance. However, challenges such as cost, scalability, and integration with legacy systems were identified as barriers to adoption. The study recommends piloting blockchain in specific MRO functions, integrating it with IoT for predictive maintenance, and collaborating with regulators to develop industry standards. Future research should focus on blockchain’s long-term cost implications, its synergy with artificial intelligence for predictive analytics, and strategies to overcome regional adoption challenges. The study underscores blockchain’s potential to modernize MRO practices and offers insights into its practical application in a developing market
The Role of Servant Leadership, Job Satisfaction, and Performance of Regional Hospital Employees
Get PDFA social organization focusing on service will continue interacting with its human members. Hospitals, as organizations specializing in health services, are faced with continuous demands to improve the quality of their services. Based on the statement above, this research aims to describe servant Leadership, job satisfaction, and employee performance. The research sample was civil servants in the Regional General Hospital who represented the respondents. To obtain a minimum sample size from the existing population, the Slovin formula was used, and the number taken was 139. The findings of this research can be a guide for researchers who are interested in similar or related fields. Data analysis techniques using descriptive analysis aim to explain each characteristic or description of the observed variables: servant Leadership, job satisfaction, and employee performance. The analysis technique applied is descriptive statistics, using frequency distribution table analysis. This approach helps provide a detailed description of each variable and its indicators. Servant Leadership in this research was determined successively by persuasive mapping, organizational stewardship, altruistic calling, wisdom, and emotional healing. Persuasive mapping is reflected in Leadership's ability to solve every problem. Job satisfaction is determined by supervision, coworkers, the job, promotion, and salary. Supervision is reflected in superiors often providing both technical and behavioral support. Organizational commitment. It is determined respectively by affective, normative, and sustainable commitment. Theoretically, the results of this research are expected to enrich human resource management literature, particularly human behavior regarding servant Leadership and job satisfaction
A Review of Different Methods Used to Compute the Drinking Water Quality Index
Get PDFThese days, the globe is very concerned about diminishing water quality (WQ) due to factors including increased industrial and agricultural activities, fast population expansion, global warming, and climate change that affect hydrological cycles. For biological purposes, freshwater availability must be sufficient, and it is also a crucial component of integrated sustainable environmental development. Among the most used instruments for characterizing WQ is the Water Quality Index (WQI). It is calculated as a single number between 0 and 100 by combining physical, chemical, and biological components. Additionally, WQI was projected as a single number that condensed the enormous number of WQ characteristics and succinctly summarized the data. Decision-making for scientists, environmental engineers, and water resource managers was facilitated by the long-term data produced by the ongoing use of WQI technology.
The primary objective of this article is to outline the top five widely used approaches for determining the drinking WQI, along with the benefits and drawbacks of each. The methods include the Weighted Arithmetic WQI (WAWQI), the National Sanitation Foundation WQI (NSF WQI), the Canadian Council of Ministers of the Environment WQI (CCME WQI), the Oregon WQI (OWQI), and the Bhargava WQI (BWQI). The study's goal and the water's characteristics should be considered when selecting one of the five approaches
Modulation and Energy Components for Speaker Recognition System
Get PDFThis paper presents a model use the modulation and energy components for speaker recognition application, that is mainly follows the short-term scenario in speech signal processing, and also introduce a parameter combination that includes the instantaneous components and the energy parameters. This will describe the importance of short-term speech analysis in estimating the modulation parameters and the role of the instantaneous energy in estimating the speaker-dependent parameters. Simply, the short-term scenario is used to, first; avoid the silent and background noise speech portions that present in speech signals, and also to benefit from the stationary concept of the short-term processing in the speech signal. The energy components, on the other hand, are adopted purely in many speech parameterisation models, such as, linear predictive coding (LPC) and Mel-frequency cepstral coefficients (MFCCs). The main ideal of our mixture parameter (or MFCC/AM-FM model) is to determined the extent of these components to contribute together in extracting the parameters that are more related to the speaker more than anything else presented in the speech signal. We evaluated both models using the text-dependent and text-independent speech corpora. The accuracy results show that the frame-based AM-FM model achieve better performance comparing with the traditional structure of the AM-FM modulation model (the model presented in [1]). The MFCC/AM-FM parameters, on the other hand, perform much better, in terms of text-dependent, comparing with the AM-FM parameters and the MFCC parameters. In the case of the text-independent, however, the MFCC/AM-FM model provide better results than the MFCC features but less performance comparing to the AM-FM modulation parameters
Optimizing the Placement of Fighter Aircraft Squadrons Using the Set Covering Problem (SCP) Method in Indonesia
Get PDFLayout and facility planning are analysis activities, forming concepts, designing systems, and realizing systems for producing goods, services, or military. Indonesia, which has direct borders with three countries, means that Indonesia is often infiltrated. Apart from Indonesia having a limited budget for implementing its work processes, its main problem is determining the location of fighter aircraft squadrons in the national defence system. If the layout of facilities can be planned well, it will determine work efficiency and survival or work success. This research applies mathematical model programming (set covering problem) to overcome this problem with the F-16 Fighting Falcon and Sukhoi SU 27/30 fighter aircraft. Then, the results of the SCP maximize covering capabilities by minimizing the average distance between air bases with the P-Median Problem (PMP). This research shows that the Indonesian Air Force needs an additional seven operational air bases to optimize the covering capabilities of fighter aircraft squadrons. In this study, the total distance travelled by the F-16 Fighting Falcon fighter aircraft was 4,479 km, with an average distance of 497.67 km. The total distance travelled by the Sukhoi SU 27/30 fighter aircraft was 11,398 km, with an average distance of 542.76 km. The average time to reach the target was 15.79 minutes. This research can be used to optimize the defence equipment in the National Air Defense System
Study of Utilization of Electronic Medical Records in Health Service Provision at the HIV Comprehensive Care Centers in Kiambu County, Kenya
Get PDFAn electronic medical record system (EMR) is a digital record of health-related data for individual patients, maintained by authorized providers. Complete and timely information is crucial for informing public health decisions and improving health service delivery, particularly for HIV/AIDS. This study assessed the utilization of EMR systems in HIV comprehensive care centers in Kiambu County, Kenya. Specifically, it examined the association and predictive influence of infrastructure, technical factors, and perceived usefulness on EMR utilization. The research adopted a descriptive cross-sectional design and applied stratified random sampling to categorize 38 health facilities based on their level of care. A sample size of 186 participants was proportionally allocated to the various strata, and data was collected through questionnaires. Analysis using SPSS version 25.0 involved Chi-square tests to examine associations between variables and logistic regression analysis to assess predictive influences. The results revealed that infrastructure (χ²=24.23, p<0.05), technical factors (χ²=62.93, p<0.05), and perceived usefulness (χ²=38.55, p<0.05) had significant associations with EMR utilization and had positive predictive influences. The study concluded that upscaling EMR utilization in HIV care clinics requires a multifaceted approach. It recommended that the County Government of Kiambu implement comprehensive training programs for EMR users, increase funding for EMR infrastructure, strengthen routine maintenance of ICT equipment, and engage ICT staff at the facility level to provide on-site support and troubleshoot the systems
Unraveling Synergies: Exploring the Intersection of Transformative Quality Education and Generative Artificial Intelligence, A Review of Literature
Get PDFIn the quickly changing field of education, there exists a need to explore and understand the intricate interplay between transformative quality education, and generative artificial intelligence. Despite increasing attention to these components individually, there is a lack of comprehensive analysis regarding their interconnected roles and potential synergies within educational contexts. This gap in understanding hinders the realization of inclusive and high-quality learning environments, as well as the effective integration of AI technologies to enhance transformative educational practices. Thus, there is a pressing need to investigate the theoretical foundations, practical implications, challenges, and opportunities associated with the convergence of transformative quality education, and generative AI in order to inform stakeholders and advance the discourse on educational innovation and sustainability. This literature review presents a comprehensive examination of the relationship between transformative quality education, generative artificial intelligence in the educational sphere. By adopting a multidimensional approach, the review intends to construct a comprehensive conceptual map that illustrates the connections and interdependencies among transformative education, quality education, and generative AI. The review identifies potential challenges and opportunities at this intersection, offering valuable insights for educators, policymakers, and technologists. By serving as a knowledge base for informed discussions and future research, this review holds implications for various stakeholders. All things considered, the knowledge gleaned from this review of the literature can help create a more thorough grasp of the revolutionary potential of generative AI in the context of high-quality education, which will eventually open the door for wise decision-making and more research in this important field
Design of MOSFET Based Boost Converter with PID and Genetic Algorithm Optimizer for Resistive Load
Get PDFThe focus of this research is the development of a DC-DC boost converter employing a polymer-based MOSFET to ensure consistent output despite variations in Resistive (R)-load. An appropriate controller for the developed converter is designed through the application of diverse optimization techniques, aiming for straightforward implementation, improved convergence quality, and enhanced computational efficiency. The optimization of Proportional-Integral-Derivative (PID) controller parameters using various algorithms is performed to enhance the converter's dynamic response in the presence of R-load. To tune the PID controller, Genetic Algorithm optimization parameters are utilized, which enhance the efficiency while including R-load. The effectiveness is measured in overshoot, rise time, settling time and peak time. The analysis also encompassed time integral domain specifications, including Integral Square Error (ISE), Integral Absolute Error (IAE), and Integral Time Absolute Value Error (ITAE). The research modeling of this technique is done in MATLAB/SIMULINK 2018 platform by considering various performance metrices.