Application of an Image-Based Model of the Elastic Modulus of Porous Thermal Barrier Coatings

Moteb Alotaibi 대한금속·재료학회 2022 METALS AND MATERIALS International Vol.28 No.8

The elastic modulus of plasma-sprayed thermal barrier coatings (TBCs), which have been utilized for gas turbine enginecomponents at elevated temperatures, has been investigated using a proposed model. The main purpose of this paper is toexplore the alterations in porous TBC microstructure that lead to alterations in its mechanical properties, including elasticmodulus. This paper investigates the effect of different types of defects, i.e., nonflat porosity, microcracks and interlamellarporosity, on the elastic modulus of porous TBC materials. The first part of this paper quantitively studies the microstructuralcharacterization of plasma-sprayed TBCs by means of an image analysis approach. The second part of this paper predictsthe elastic modulus of plasma-sprayed TBCs based on microstructural changes, i.e., defects. The volumetric fraction of differenttypes of defects and their shapes and orientations are also taken into account. It is found that both microcracks andinterlamellar porosity exhibit a crucial optimization on the elastic modulus of porous TBCs, while nonflat porosity showsa lesser effect on the elastic modulus. The predicted data of the proposed model show relatively good agreement with FEAmodel results and experimentally measured results. These simulation results could help to further the understanding of theimpact of porous TBC microstructural alterations on elastic modulus.

KAB: Knowledge Augmented BERT2BERT Automated Questions-Answering system for Jurisprudential Legal Opinions

Alotaibi, Saud S.,Munshi, Amr A.,Farag, Abdullah Tarek,Rakha, Omar Essam,Al Sallab, Ahmad A.,Alotaibi, Majid International Journal of Computer ScienceNetwork S 2022 International journal of computer science and netw Vol.22 No.6

The jurisprudential legal rules govern the way Muslims react and interact to daily life. This creates a huge stream of questions, that require highly qualified and well-educated individuals, called Muftis. With Muslims representing almost 25% of the planet population, and the scarcity of qualified Muftis, this creates a demand supply problem calling for Automation solutions. This motivates the application of Artificial Intelligence (AI) to solve this problem, which requires a well-designed Question-Answering (QA) system to solve it. In this work, we propose a QA system, based on retrieval augmented generative transformer model for jurisprudential legal question. The main idea in the proposed architecture is the leverage of both state-of-the art transformer models, and the existing knowledge base of legal sources and question-answers. With the sensitivity of the domain in mind, due to its importance in Muslims daily lives, our design balances between exploitation of knowledge bases, and exploration provided by the generative transformer models. We collect a custom data set of 850,000 entries, that includes the question, answer, and category of the question. Our evaluation methodology is based on both quantitative and qualitative methods. We use metrics like BERTScore and METEOR to evaluate the precision and recall of the system. We also provide many qualitative results that show the quality of the generated answers, and how relevant they are to the asked questions.

Using Machine Learning to Improve Evolutionary Multi-Objective Optimization

Alotaibi, Rakan International Journal of Computer ScienceNetwork S 2022 International journal of computer science and netw Vol.22 No.6

Multi-objective optimization problems (MOPs) arise in many real-world applications. MOPs involve two or more objectives with the aim to be optimized. With these problems improvement of one objective may led to deterioration of another. The primary goal of most multi-objective evolutionary algorithms (MOEA) is to generate a set of solutions for approximating the whole or part of the Pareto optimal front, which could provide decision makers a good insight to the problem. Over the last decades or so, several different and remarkable multi-objective evolutionary algorithms, have been developed with successful applications. However, MOEAs are still in their infancy. The objective of this research is to study how to use and apply machine learning (ML) to improve evolutionary multi-objective optimization (EMO). The EMO method is the multi-objective evolutionary algorithm based on decomposition (MOEA/D). The MOEA/D has become one of the most widely used algorithmic frameworks in the area of multi-objective evolutionary computation and won has won an international algorithm contest.

REGULARITY AND MULTIPLICITY OF SOLUTIONS FOR A NONLOCAL PROBLEM WITH CRITICAL SOBOLEV-HARDY NONLINEARITIES

Alotaibi, Sarah Rsheed Mohamed,Saoudi, Kamel Korean Mathematical Society 2020 대한수학회지 Vol.57 No.3

In this work we investigate the nonlocal elliptic equation with critical Hardy-Sobolev exponents as follows, $$(P)\;\{(-{\Delta}_p)^su={\lambda}{\mid}u{\mid}^{q-2}u+{\frac{{\mid}u{\mid}^{p{^*_s}(t)-2}u}{{\mid}x{\mid}^t}}{\hspace{10}}in\;{\Omega},\\u=0{\hspace{217}}in\;{\mathbb{R}}^N{\backslash}{\Omega},$$ where Ω ⊂ ℝ^N is an open bounded domain with Lipschitz boundary, 0 < s < 1, λ > 0 is a parameter, 0 < t < sp < N, 1 < q < p < p^∗_s where $p^*_s={\frac{N_p}{N-sp}}$, $p^*_s(t)={\frac{p(N-t)}{N-sp}}$, are the fractional critical Sobolev and Hardy-Sobolev exponents respectively. The fractional p-laplacian (-∆_p)^su with s ∈ (0, 1) is the nonlinear nonlocal operator defined on smooth functions by $\displaystyle(-{\Delta}_p)^su(x)=2{\lim_{{\epsilon}{\searrow}0}}\int{_{{\mathbb{R}}^N{\backslash}{B_{\epsilon}}}}\;\frac{{\mid}u(x)-u(y){\mid}^{p-2}(u(x)-u(y))}{{\mid}x-y{\mid}^{N+ps}}dy$, x ∈ ℝ^N. The main goal of this work is to show how the usual variational methods and some analysis techniques can be extended to deal with nonlocal problems involving Sobolev and Hardy nonlinearities. We also prove that for some α ∈ (0, 1), the weak solution to the problem (P) is in C^1,α(${\bar{\Omega}}$).

Auto-Configuration Downlink Transmission Power Approach For Femtocell Base Station

Alotaibi, Sultan International Journal of Computer ScienceNetwork S 2022 International journal of computer science and netw Vol.22 No.4

Femtocells are being incorporated into heterogeneous networks in order to increase the network capacity. However, intensive deployment of femtocells results in undesired interference, which lowers the system's performance. Controlling the femtocell transmission power is one of of the aspects that can be addressed in order to mitigate the negative effects of the interference. It may also be utilized to facilitate the auto-configuration of the network's conductance, if necessary. This paper proposes the use of an auto-configuration technique for transmission power. The suggested technique is based on the transmission power of macrocells and the coverage provided by femtocells. The simulation findings show that the network's capacity has increased, and the amount of interference has decreased.

Theories, Frameworks, and Models of Using Artificial Intelligence in Organizations

Alotaibi, Sara Jeza International Journal of Computer ScienceNetwork S 2022 International journal of computer science and netw Vol.22 No.11

Artificial intelligence (AI) is the replication of human intelligence by computer systems and machines using tools like machine learning, deep learning, expert systems, and natural language processing. AI can be applied in administrative settings to automate repetitive processes, analyze and forecast data, foster social communication skills among staff, reduce costs, and boost overall operational effectiveness. In order to understand how AI is being used for administrative duties in various organizations, this paper gives a critical dialogue on the topic and proposed a framework for using artificial intelligence in organizations. Additionally, it offers a list of specifications, attributes, and requirements that organizations planning to use AI should consider.

Food Security through Smart Agriculture and the Internet of Things

Alotaibi, Sara Jeza International Journal of Computer ScienceNetwork S 2022 International journal of computer science and netw Vol.22 No.11

One of the most pressing socioeconomic problems confronting humanity on a worldwide scale is food security, particularly in light of the expanding population and declining land productivity. These causes have increased the number of people in the world who are at risk of starving and have caused the natural ecosystems to degrade at previously unheard-of speeds. Happily, the Internet of Things (IoT) development provides a glimmer of light for those worried about food security through smart agriculture-a development that is particularly relevant to automating food production operations in order to reduce labor expenses. When compared to conventional farming techniques, smart agriculture has the benefit of maximizing resource use through precise chemical input application and regulation of environmental factors like temperature and humidity. Farmers may make data-driven choices about the possibility of insect invasion, natural disasters, anticipated yields, and even prospective market shifts with the use of smart farming tools. The technical foundation of smart agriculture serves as a potential response to worries about food security. It is made up of wireless sensor networks and integrated cloud computing modules inside IoT.

LTE Packet Scheduling with Bandwidth Type Consideration

Alotaibi, Sultan International Journal of Computer ScienceNetwork S 2022 International journal of computer science and netw Vol.22 No.4

LTE (Long-Term Evolution, sometimes known as 4G LTE) is a wireless high-speed data communication technology for mobile phones and data terminals. The Packet Scheduler (PS) is an important component in improving network performance. Physical Resource Blocks (PRBs) are assigned to associated User Equipment by the packet scheduler (UEs). The primary contribution of this study is a comparison of the eNodeB throughput between a suggested method and the Round Robin (RR) Algorithm. The RR Algorithm distributes PRBs among all associated UEs without taking channel circumstances into account. In this research, we present a new scheduling method that takes into account the number of PRBs and associated UEs and produces higher throughput than the RR algorithm.

Fractional Frequency Reuse (FFR) Usability Improvement in LTE Networks

Alotaibi, Sultan International Journal of Computer ScienceNetwork S 2022 International journal of computer science and netw Vol.22 No.4

Femtocell networks can be a potential method for increasing the capacity of LTE networks, especially in indoor areas. However, unplanned deployment of femtocells results in co-tier interference and cross-tier interference problems. The interference reduces the advantages of implementing femtocell networks to a certain extent. The notion of Fractional Frequency Reuse (FFR) is proposed in order to reduce the impact of interference on the system's performance. In this paper, a dynamic approach for efficiently partitioning the spectrum is suggested. The goal is to enhance the capacity of femtocells, which will improve the performance of the system. The suggested strategy allocates less resources to the macrocell portion of the network, which has a greater number of femtocells deployed to maximize the utilization of available resources for femtocell users. The spectrum division would be dynamic. The proposed strategy is evaluated through a simulation using MATLAB tool. In conclusion, the results showed that the proposed scheme has the potential to boost the system's capacity.

Autonomous Transmission Power Adjustment Strategy for Femtocell Base Station

Alotaibi, Sultan International Journal of Computer ScienceNetwork S 2022 International journal of computer science and netw Vol.22 No.4

Femtocells have recently been recognized for their potential to boost network capacity, improve end-user QoS and throughput, and do so at a cheap cost and with ease of implementation. The use of femtocells in indoor environments, such as residential buildings with neighboring homes, is becoming more popular. Femtocells are subject to interference from other femtocells, and the unwanted effects of interference are amplified when femtocells are deployed in close proximity to one another. As a consequence, the network's overall performance is degraded to a significant degree. One of the strategies that is thought to be effective in reducing the impact of interference is altering the transmission power of the femtocells. In this paper, a dynamic downlink transmission power of femtocells is suggested. In accordance with the observed cost function unit, each femtocell automatically changes its transmission power. If a femtocell causes too much interference for its neighbors, its transmission power level will be limited by that interference's rate. A simulation experiment is conducted to validate the effectiveness of the suggested system when compared with other schemes. When compared to previous schemes, which are addressed in this study, the numerical results show that the proposed strategy could provide more capacity while also ideally mitigating the influence of interference among co-channel deployed femtocells.