This paper presents the development of an advanced system designed to efficiently process Arabic queries in today’s data-driven landscape. By using the T5 sequence-to-sequence model developed by Google and fine-tuning it specifically for transforming textual and verbal input into SQL queries, the system becomes adept at accurately comprehending and interpreting Arabic queries.

The resulting system serves as a user-friendly tool that automates the generation of SQL queries. Users can input their queries in written or recorded Arabic utterances, eliminating the need for manual translation and query construction.

This involved fine-tuning T5 models on a SQL dataset, splitting the dataset, tokenizing it, and setting training parameters. The implementation phase included loading the fine-tuned model, which incorporated PICARD to generate valid queries effectively. This paper also explores the impact of Arabic translation on the performance and accuracy of the model.

The optimal testing on test set accuracy achieved was 63.11%, the real-world testing accuracy: T5-base without PICARD scored 56.96% and 51.36% on English and Arabic questions, respectively, while T5-large with PIARCD scored 77.74% and 70.34% on English and Arabic questions.

ABSTRACT

This article presents another method to improve the performance

and efficiency of a gas-fired power plant in Al-Zawia, Libya. In

order to improve power plant efficiency and increase power, the

principle of a heat recovery steam generator (HRSG), which is

mainly based on the waste heat energy of exhaust gases generated

by a simple gas turbine unit, is a method that can be used for

improvement. The present system was simulated using Aspen

HYSYS software. For validation purposes, the simulation results

were compared with the actual operating data, net power and

thermal efficiency of the cycle under the same conditions. These

results show a high level of agreement between theoretical and

practical data. This agreement enables and provides good

implementation to use this software to simulate an entire combined

cycle. In addition, operating parameters that influence power plant

performance were examined. The results show that the combined

cycle improved the thermal efficiency and net power output by

49.8% and 50%, respectively, under the same operating conditions.

The results also showed that compressor pressure ratio and inlet air

temperature have significant effects on thermal efficiency and net

power produced in both simple and combined power plants

Net Zero Energy (NZE) buildings play a crucial role in meeting the Sustainable Development Goals (SDG) and creating environmentally friendly residential areas. These buildings are designed to generate as much energy as they consume, resulting in a net balance of zero energy consumption from the grid. By integrating innovative technologies and sustainable design principles, NZE buildings minimize their carbon footprint and contribute to a more sustainable future. The acquired result has been presented and discussed. The concept of Net Zero Energy Buildings (NZEBs) has gained significant attention in recent years as a crucial strategy for achieving sustainability in the built environment. NZEBs are designed to produce as much energy as they consume, resulting in a net energy balance of zero over a specified period.

Abstract: Network operators are confronted with the demanding requirements resulting from the evolution of IP networks. As a result, it has become necessary to provide rigorous Service Level Agreements (SLAs) that are in line with these requirements. However, traditional IP networks lack the necessary flexibility, scalability, and manageability to meet these demands. In order to address these limitations, the segment routing (SR) architecture has been developed. SR is based on source-routing and tunneling paradigms, which enable IP/MPLS and IPV6 networks to operate in a simplified and more scalable manner. The focus of this paper is on network protection (resiliency) using Topology Independent Loop-Free Alternatives Fast Re-Route (TI-LFA FRR) using MPLS as the underlying technology. SR overcomes the limitations of previous network protection mechanisms in terms of coverage and optimal path selection. To show the effectiveness of SR TI-LFA in comparison to its predecessor, Remote Loop-Free Alternate (rLFA), we have implemented various scenarios. These scenarios are designed to highlight the superior capabilities of TI-LFA. 

Abstract—Fault detection and classification is critical to the reliability of modern control systems in different industries, where detecting and classifying faults in operational processes are very important things while failure to detect and classify them, may cause irreparable damage. In this paper, fault detection and classification approach is presented. The first step, multi stage recursive least squares parameter estimation approach for controlled autoregressive autoregressive moving average systems (CARARMA) is developed with a view to estimate the parameters of the system, additionally, improve the effectiveness of the computation. By means of multi stage approach, the (CARARMA) system is decomposed into three simple identification models, and the parameters of each simple model is identified one by one. These parameters estimated by this approach are referred to as features, and not all of them have the same useful data about the system. In order to select the valuable features and improve a classification accuracy, the Linear Discriminant Analysis (LDA) approach based on scattering matrices is applied for dimension reduction. The classification between these reduced classes is done based on the Naive Bayes classifier. Finally, the obtained results explain the performance of this proposed approach.

The classical Model Predictive Control (MPC) is still considered in many industrial applications, although advanced control methods have seen  significant development over the last few years. However, a lot of MPC strategies still suffer from  robustness to cope with a variety of process dynamics. For the MPC controller to work effectively,  it must be properly tuned. However, MPC is challenging and there is no ideal analytic method to  obtain exact solutions that result in the best desired responses. Based on that, this paper  investigate the robustness performance for a MPC tuning strategy. Three formulae were derived  (Proposed , Proposed  and Proposed ). These formulae are used for calculating the suppression coefficient. The three  formulae were derived by fitting the optimal empirical suppression coefficients for varies process  dynamics commonly found in industry. Simulation results show that the use of the proposed strategy results in good performance compared to other strategies previously proposed. The proposed   strategy also demonstrated a robust performance with respect to modelling errors of process  parameters. The results demonstrate the effectiveness and validity of proposed strategy when  compared with conventional strategies.

Abstract:

This paper explores the utilization of ANSYS software to replace traditional stainless steel in

Liquid Natural Gas (LNG) cylinders with a lightweight composite material called E Glass Epoxy.

The goal is to reduce the cylinder's weight through finite element analysis using ANSYS, adhering

to Libyan market standards. Stresses under internal pressure are analyzed and compared with

analytical solutions for steel cylinders. The study highlights weight reductions for steel and

composite LNG cylinders, emphasizing the practicality, utility, and safety considerations in

addressing the challenges faced by the Indian Gas supply system, especially for housewives

dealing with heavy stainless steel cylinders.

This project aims to provide a user-friendly alternative, maintaining gas storage efficiency while

significantly reducing cylinder weight

The quest for reliable water access has been a critical endeavor throughout history, and Rujban

City is no exception. Faced with the challenges of aging infrastructure and reliance on external

water sources, Rujban is turning towards technological innovation for solutions. This paper

outlines the design of the communication component within the Idref Automated Control System

2 (IACS II), a significant advancement in the automation of Rujban's water distribution system.

This system innovatively connects the city's central distributed tank to three distributed tanks via

a robust wireless communication network, while maintaining a wired connection to the Idref

collection tank, the main control station, and associated monitoring rooms and pumps. The system

employs microcontroller-based automation to manage water levels, control signals, and monitor

pump activity and potential leaks, with data displayed on an LCD screen. This approach is poised

to dramatically improve the efficiency and reliability of water distribution in Rujban City, marking

a key step forward in addressing its water supply challenges.

Abstract As more and more people turn to the cloud for their personal and professional purposes, cloud computing has become essential for the majority of users. Given the increased demand for cloud virtualization, the datacenter needs to be able to accommodate more virtual machines (VMs) that are housed on its servers. A datacenter employing old technology may accommodate up to 4096 VLANs, which would restrict the number of tenants it could serve. Spanning-Tree Protocol (SPT) is used by VLANs to remove loops, or duplicates, which block half of the routes and waste available bandwidth. The Virtual Extensible LAN (VXLAN), an emerging technology, must be used from there. It permits network segmentation similar to that of regular VLANs without obstructing traffic or reducing scalability. This study outlined both established and novel approaches and then clarified how to use them for data center topology. It also covered the drawbacks of utilizing conventional technologies. The benefits of cutting-edge technology and its superior influence on datacenter bandwidth utilization. To demonstrate how the new technology enhances data center performance, these technologies were finally replicated using the Eve emulator.

This paper investigates the effects of applying fuzzy techniques to artificial neural networks (ANN) for

the classification of biological data. A fuzzy neural networks (FNNs) model was proposed and evaluated

as a system for image classification. This system involved the process of collecting dataset, image

processing and image classification. Patch-based technique is used to present images to the neural

network. Feed-Forward Backpropagation neural networks are used to build the system. Fuzzy Min-Max

Neural Networks (FMNN) approach was used to synthesize Fuzzification and neural networks to generate

fuzzy neural networks that can handle imprecision and uncertainty. The approach is evaluated using

images from the data portal (Papers with Code) website. Experimental results have shown an improvement

in the performance of fuzzy neural networks compared with neural networks.