American Scientific Research Journal for Engineering, Technology, and Sciences

Life Cycle of a Low Mass Stars

Sabir Sadiq — 2023-05-17

In the present work, I shall explain the gravity mechanism and life cycle of a low mass Stars. For this purpose, some mathematical equations, and MATLAB Program could be used to draw the shape of a gravity as a dark fabric distortion in three dimensions under the stress of a Solar mass Stars from the Birth to Death. Stellar structure and evolution are acting directly on the distortion of a dark fabric matter and energy. The Gravity is acting directly on the Formation, Structure, and Evolution of a Solar Mass Stars. Dark Fabric Geometry was curved and distorted differently under the stress of an ordinary Stars like the Sun, and Compact Stars. White dwarfs and black dwarfs are two dense and compact stars where dark fabric is warping strongly under their stress. Dwarf star is other type of a low mass Stars where its mass is very low to produce energy from nuclear fusion at its Centre.

Robust Feature Sets for Implementation of Classification Machines

Binesh T — 2023-04-20

Classification Machines have evolved over a lot during recent times, in the field of engineering and sciences. Various classification schemes have been developed, taking into account, the aspect that can be optimized to give maximum system performance. The feature set in a classifier system is very significant, since it determines the efficiency and performance of the machine. Three powerful feature sets possessing robust classifying capabilities are discussed in this paper. Cepstral coefficient analysis based Kruskal-Wallis H statistic, F-test statistic and Discrete Sine Transform based features are found to be very effective for detection and classification of signals. Simulation results for typical data set are also presented in this paper. Statistical estimators, Neural Network and Hidden Markov Model based classifiers, along with various deep learning algorithms can be incorporated along with these feature sets to implement an efficient classifying machine. Typical results based on these feature sets are also presented for different signal sources.

Urban Heat Island (Uhi) Effect: The Rise of Land Surface Temperature in Cebu City, Philippines

Menzuela Ancheta-Comora — 2023-04-20

Temperature differences between the urban and surrounding areas have resulted from rapid urbanization. This study tries to systematically understand the urban heat island phenomenon in Cebu City by determining the land surface temperature using satellite images in 2010 and 2018. Land Surface Temperature (LST) was determined using the Surface Energy Balance Algorithm for Land (SEBAL) approach. The results were correlated to spatial metrics to identify its influence on the spatial variation of LST in Cebu City. Results indicated that the mean LST in Cebu City increased from 22⁰C to 25⁰C from 2010 to 2018. In 2018, the built-up area contributed the most LST, followed by forest and bare land, with 28.40 0C, 26.25 0C, and 25.85 0C, respectively. The results indicated that the landscape metrics are highly negatively correlated to LST, mainly attributed to the increase in forest area in Cebu City.

Mathematical Analysis of Regression Model Epidemiology

Prof. Dr. Sumit Kumar Banerjee — 2023-04-24

Statistical modeling techniques, specifically regression line analysis have become important analytical tools and are contributing immensely to the field of epidemiology. However, many users do not understand their effective use and applications. Underlying epidemiological concepts and not the statistics should govern or justify the proper use and application of any modeling exercise. Main utility of the regression line analysis lies in its ability to provide a general but practical conceptual framework for casual problems, explaining and evaluating the role of biases, confounders and effect modifiers. Successful modeling of complex data is a part science, part statistics and part experience, but the major part is logic or common sense. Findings of this research article focuses on the contributions of regression analysis towards the pedagogical study of epidemiological models by enhancing the research process and serving as an effective tool for communicating findings to public health managers and policymakers and fostering interdisciplinary collaboration.

Transforming Smart Cities with Artificial Intelligence: Opportunities, Challenges, and Future Implications

Imad Hanna — 2023-05-22

This paper explores the impact of artificial intelligence (AI) on smart cities. With the rapid development of AI, its applications in smart cities have become increasingly important in enhancing urban development, improving public services, and creating sustainable and efficient urban environments. The paper first provides an overview of smart cities and AI, highlighting the importance of studying the impact of AI on smart cities. It then examines the role of AI in smart cities, including its definition, applications, and benefits. The paper also analyzes the impact of AI on smart city development, including changes in urban planning and design, transportation and traffic management, energy efficiency, and public safety and security. However, the potential risks and challenges of AI in smart cities, such as ethical and privacy concerns, job displacement, and cybersecurity risks, are also discussed. Finally, the paper explores the future of AI in smart cities, including opportunities for further innovation, collaboration between public and private sectors, and potential impact on urban lifestyles and citizen engagement. The paper concludes with a summary of the key points and implications for future research and policy-making.

Grain Yield of Rice, Corn, and Sorghum to Low External Input Agriculture Practices in Maliana, Bobonaro, Timor Leste

Agostinho C. Moniz — 2023-05-05

A farmers’ field yield trial during the 2018 dry season was conducted in Maliana, Bobonaro District, Timor Leste to evaluate the compatibility of selected hybrid and inbred varieties of rice, maize, and sorghum to low external input crop management practices common to subsistence farmers in the region. In rice, grain yield performance as influenced by genotype (hybrid or inbred) and planting density (single or double row spacing) was assessed by measuring grain yield and selected agronomic traits. In rice, grain yield was not significantly different, between hybrid and inbred varieties, but higher planting densities gave 17-27% advantage for hybrids and 36-45% for inbred varieties. The observed yield from farmers’ field was, however, 60-70% lower than yield obtained from experimental fields. Agronomic traits (plant height, tiller, panicle, and spikelet counts) were found to have very strong genotype x planting density interaction effects, and although post-hoc analyses revealed marginal differences on selected yield-related components between the two planting densities, these differences were not statistically significant, and did not contribute to improvement in rice grain yield. Hybrid and inbred varieties of maize and sorghum showed comparable yield levels in two independent yield trials, and although agronomic traits showed significant differences between varieties, these did not account for any yield advantage.

Mapping Groundwater Levels in Erbil Basin

jwan sabah mustafa — 2023-04-20

In the Erbil Basin, which is located in Kurdistan Region at northern part of Iraq, several production wells have been selected for monthly monitoring of groundwater levels. The continuous depletion of groundwater levels has been recorded due to uncontrolled exploitation from both legal and illegal wells that poses a major problem in selected Basin, which is classified as arid and semi-arid regions. Accurate prediction of groundwater depth and elevation maps is crucial for the development of effective groundwater management strategies in the aquifer system of the area. Depth to groundwater measures for each of the 55 wells that distributed across the North, Central, and South sub-basins of Erbil, also mapped and compared with wells data that are recorded periodically by the Directorate of Erbil Groundwater. The methodology of this study is involved mapping groundwater tables for the measured wells in (2022) with surveying wells coordinates as field observations, and compare with data of groundwater tables in (2004) that archived by groundwater directorate. This study employs high-accuracy surveying techniques for the selected wells and utilizes geographic information systems (GIS) as a successful tool for mapping groundwater levels using both Kriging and IDW interpolation methods. The results are indicated successfully that groundwater tables have sudden drawdown during these (18) years, the main reasons behind that is drilling numerous wells without planning and lack of management of the wells system in the study area. Meanwhile, Erbil basin required better planning and management of groundwater resources. The study concludes that there is lack in groundwater management need to keep the sustainability of this vital resources, and observing monthly groundwater levels need to be connected with high accuracy sensor inside observation wells not manually measuring groundwater levels by damaged sounders. Unfortunately, there is no observation wells inside Erbil basin, the recorded data are within production wells that cannot represent as actual levels of the groundwater. The main objective of this study is to present the actual problems in the study area by create the maps of the groundwater table for the selected basin and to be used as a basic plan in developing strategies for effective management and planning of Erbil groundwater resources. And also employed to protect aquifer storage and prevent depletion of groundwater resources.

Bridging the Gap Between Stakeholder and Software Products: A Review of Software Requirement Engineering Techniques

Nzechukwu Chizaram Otuneme — 2023-05-30

Effective software requirement engineering plays a crucial role in bridging the gap between stakeholders and software products. The success of any software project heavily relies on accurately capturing, analyzing, and documenting stakeholders' needs and expectations. This article provides a comprehensive review of various software requirement engineering techniques that facilitate the alignment of stakeholder requirements with software product development. Software requirements are extracted from a variety of stakeholders, but the decision of "what to develop" is a difficult one. Stakeholders' lack of clarity about what they want makes requirement elicitation a difficult and vital task. It explores the significance of understanding stakeholders' perspectives, discusses popular requirement engineering approaches, and highlights their strengths and limitations. The article concludes by emphasizing the importance of selecting appropriate requirement engineering techniques based on the project's context and offers recommendations for future research in this domain.