International Journal of Advances in Applied Sciences
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Modern research of using alternative energy resources in Azerbaijan
Get PDFThe article provides a comprehensive analysis of modern trends and prospects for the use of solar batteries in various sectors of the economy and the agricultural sector. The purpose of this article is to analyze the possibility of energy saving for a private residential building in Gobustan using solar energy storage in a greenhouse extension and a heat pump to transfer heat to the heating system. The calculation showed that in the coldest month, December, the potential of solar thermal energy is 15-38% of the required heat demand, depending on the material used in the extension design. In March and April, excess heat is generated, which can be used for hot water supply needs. Thus, for an individual residential building, the use of solar heat accumulated in a greenhouse extension is relevant as an additional source of heat for the heating system. Surface density of solar radiation flux, W/m2: surface density of direct solar radiation flux: 1,680 (November), 1,530 (December), 1,870 (January), 2,730 (February), 3,270 (March), 3,180 (April); Surface density of diffuse solar radiation flux: 650 (November), 450 (December), 480 (January), 680 (February), 1180 (March), 1,830 (April)
Determination of soil salinization by hyperspectral remote sensing in the Shirvan Plain
Get PDFThe determination of soil salinization in the Shirvan Plain, considered the main agricultural zone of Azerbaijan, negatively affects the productivity of agricultural crops. Based on 10 m Sentinel-2 images on Google Earth Engine platforms and by examining SI1, green-red band normalized difference vegetation index (GRNDVI), green normalized difference vegetation index (GNDVI), normalized difference vegetation index (NDVI), and difference vegetation index of the environment (DVI), four remote sensing salinity monitoring index models, S1DI1, S1DI2, S1DI3, and S1DI4, were constructed to extract soil salinity information in the Shirvan Plain in combination with the measured electrical conductivity. The results show that the overall classification accuracy of S1DI1 (SI1-GRNDVI), S1DI2 (SI1-GNDVI), S1DI3 (SI1-NDVI), and S1DI4 (SI1-DVI) models for salinity monitoring are 82.35%, 83.10%, 81.96%, and 79.25%, respectively
Effectiveness of dashboard as a work progress scheduling, monitoring, and decision-making in construction projects
Get PDFScheduling, monitoring, and decision-making are important factors in determining the general achievement of sustainable construction. Therefore, this study was conducted to determine the effectiveness of a dashboard as a measuring tool for construction project scheduling, monitoring, and decision-making. A survey with a Likert scale (5 scale) on each viewpoint, including planning, oversight, and independent direction, of 15 respondents from project executors and 7 respondents from supervisors was used as instrumentation. The results showed that the dashboard was evaluated with a value of 92.25 among executors and supervisors linked to product characteristics. Executors also used the scheduling dashboard with a value of 91.73, and the feature of employing the concept for supervision was appropriate as a measuring instrument, scoring 92.15. Furthermore, the final step was the aspect of using the dashboard for decision-making, which was tested and used with a value of 88.14. The use dashboard model is an effective tool for work progress scheduling, monitoring, and decision-making in construction projects
Big data assisted eco-learning environment framework for inclusive education
Get PDFBig data is profoundly changing education under inclusive education. Classroom interaction, a vital component in education, is gaining increased emphasis, driving research into learning environments that better meet interaction needs. Therefore, exploring the construction of a big data-assisted eco-learning environment for classroom interaction is a prospective study. This research focuses on constructing a big data-assisted ecological learning environment based on affordance theory. It examines the relationship among learning environment, classroom interaction, and learning outcomes, using SmartPLS for validation. Through controlled experiments, surveys, teacher-student interaction analysis, and interviews, the study explores learner behavior data. Findings show the big data-assisted eco-learning environment enhances English classroom interaction, thereby further improving learning outcomes, across dimensions like learning space, resource accessibility, technical support, and emotional support. Integrating big data with ecological theory offers insights into educational digitization, supporting flexible classroom interaction, and promoting education equity, inclusivity, and sustainable education through data-driven resource management
Digital transformation COVID-19 era: startup strategies for technology, management, and people
Get PDFStartups are not an exception to the fast acceleration of digital transformation across sectors caused by the COVID-19 pandemic. Digital transformation has served as a strategic lever for startups to improve operations, enhance customer experiences, and develop new business models. This study investigates how startups in Western Visayas, Philippines, navigated the pandemic while undergoing digital transformation. Our primary objective is to provide a comprehensive understanding of digital transformation, outlining its key components. By analyzing relevant business literature, we identified three core areas: i) technology, ii) management, and iii) people. This research explores the strategies employed by startups to embrace digital transformation, the technological tools they utilize, and the critical role of effective leadership and organizational culture in successful transformation initiatives. Data was collected through an online survey administered on Qualtrics. The findings reveal that most startups adapted their business models, leveraged social media platforms, and relied on their customer base for support during the pandemic. This study contributes to the existing knowledge base by offering insights into the digital transformation landscape in the Philippines. Furthermore, it enhances our understanding of the strategies and processes required to address the challenges of the digital age
Fuzzy analytic hierarchy process for analysis of barriers to halal supply chain adoption in Indonesia
Get PDFThe increasing awareness of the importance of halal certification has prompted companies to evaluate the barriers to adopting the halal supply chain. While this adoption has the potential for significant benefits, various barriers must be investigated. This study examines the barriers to adopting halal supply chains in small and medium-sized food enterprises (SMEs). The fuzzy analytical hierarchy process (fuzzy AHP) assesses and weighs the 30 identified barriers. The results showed that the main barriers to adopting a halal supply chain include understanding and awareness of the importance of halal certification, support from the government and related institutions, and companies' internal readiness to implement halal standards. In addition, other significant barriers were high certification costs, lack of funds to promote the halal industry, lack of willingness to adopt and implement halal in the supply chain, and lack of technology costs to manage supply chain processes by halal standards. The implications of this study suggest the need for better support strategies from the government and relevant agencies, as well as awareness and understanding-raising efforts among SMEs to overcome these barriers and facilitate the adoption of halal supply chains
Evaluation of 6 MV photon beam characteristics on Varian Clinac iX: a Monte Carlo study
Get PDFThis work aims to study the characteristics of photon beams through phase space file (PSF) analysis using Monte Carlo (MC) simulation. 6 MV photon beams from the Varian Clinac iX were simulated using PRIMO software. The beam parameters were validated by evaluating the percentage depth dose and dose profile. A full PSF was scored at the downstream end of the linear accelerator (LINAC) upper and lower parts and analyzed to determine the beam fluence profile, energy fluence profile, angular distribution, and spectral distribution. The results show that within PSF 1, the photon beam has an average scattering angle of 10.74° and a mean energy of 1.18 MeV. In PSF 2, the average scattering angle decreases to 2.63° while the mean energy increases to 1.50 MeV. The field size variation at 20×20, 30×30, and 40×40 cm2 affects both the angular and spectral distribution of the photon beam. The photon beam in PSF 2 exhibits an average scattering angle of 4.56, 6.31, and 6.66°, with corresponding mean energy values of 1.40, 1.32, and 1.30 MeV, respectively. These findings show that as the field size increases, the photon beam scatters at a larger angle while the energy decreases
Optimizing VR-UX: analysis and adaptive recommendations for enhancing immersion and reducing motion sickness
Get PDFThis study presents an adaptive recommendation framework to enhance comfort and immersion in virtual reality (VR) by actively reducing motion sickness. Unlike prior research that views VR user experience (UX) as static, this approach integrates statistical analysis with dynamic system design. Using a Kaggle dataset of 1,000 entries, we applied descriptive statistics, Spearman correlation, Kruskal-Wallis tests, and regression to explore relationships among session duration, motion sickness, immersion, headset type, and user demographics. Findings show that session duration alone does not significantly predict motion sickness or immersion (R²=0.00, p>0.05), but certain user profiles, such as individuals over 30 using PlayStation VR, are more prone to discomfort. These insights inform a four-module framework: user profiling, real-time duration monitoring, rule-based adaptation logic (such as slowing navigation speed or adding a virtual nose for visual stability), and personalized in-VR recommendations. The system is compatible with Unity and Unreal Engine and integrates with commercial headset software development kits (SDKs). Future validation will use A/B testing, standardized questionnaires, simulator sickness questionnaire /immersion presence questionnaire (SSQ/IPQ), and physiological metrics. This work shifts VR design toward personalized, responsive systems that prioritize user well-being and immersive engagement
Design and analysis of a portal frame test rig for vertical load testing of goalpost pipeline support
Get PDFPipe support is a crucial infrastructure in the oil and gas industry, requiring robust designs to withstand various loads and maintain operational stability. While numerical analysis is commonly used to assess the interaction between pipelines and supports, experimental testing remains essential for validation. However, field testing is often costly and difficult due to safety constraints. To overcome this, a reliable test rig with minimal deflection is needed to ensure accurate experimental results. This study uses finite element analysis (FEA) to evaluate both a goalpost pipeline support and a newly developed portal frame test rig. The test rig was analyzed under two conditions: the failure load of the goalpost support and an amplified load with a factor of 2.5 to simulate unexpected scenarios. Results show the test rig can safely withstand loads up to 40 kN, meeting the EN 1990 safety factor requirement of 1.5. Furthermore, critical components remained within the deflection limit specified by the British Constructional Steelwork Association (BCSA), which is under L/1,000 of the beam length. These results confirm the structural integrity and suitability of the portal frame test rig for accurate testing of the goalpost pipeline support structure
Development of a leakage detection and alert system for liquefied petroleum gas via a mobile application
Get PDFNowadays, ensuring the comfort and safety of house users is a top priority, and this may be accomplished by implementing smart technology to lead a convenient and safe life. Leakage of liquefied petroleum gas (LPG), which is mostly utilized in the home kitchen for cooking, is one of the frequent risks. Using a gas sensing device, a gas control system, and wireless communication units, the goal of this study is to create an LPG gas leakage warning and management system to prevent the gas from exploding by detecting the leak. When LPG gas is brought near the sensor, it detects the leakage and the buzzer is activated by activating the audio-visual alarm and closing the gas cylinder valve. The system also generates alert messages and sends them to the fire station when the LPG gas leakage has reached a critical level. Testing results of the proposed LPG leakage system show a satisfactory performance of the developed device with a quick response to LPG gas leakage. In addition, powerful audio and visual alarms are activated. An immediate message was sent to homeowners and the fire station department regarding the leakage incident to prevent the risk of gas leakage