Design of GCSC Stabilizing Controller for Damping Low Frequency Oscillations

This paper presents a systematic procedure for modeling and simulation of a power system equipped with FACTS type Gate Controlled Series Compensator (GCSC) based stabilizer controller. Single Machine Infinite Bus (SMIB) power system was investigated for evaluation of GCSC stabilizing controller for enhancing the overall dynamic system performance. PSO algorithm is employed to compute the optimal parameters of damping controller. Eigenvalues of system under various operating condition and nonlinear time domain simulation is employed to verify the effectiveness and robustness of GCSC stabilizing controller in damping low frequency oscillations (LFO) modes

Artificial lift selection methods in conventional and unconventional wells: a summary and review from old techniques to machine learning applications.

Artificial lift (AL) selection is an important process in enhancing oil and gas production from reservoirs. This article explores the old and current states of AL selection in conventional and unconventional wells, identifying the challenges faced in the process. The role of various factors such as production and reservoir data and economic and environmental considerations is highlighted. The article also examines the use of machine learning (ML) techniques in the AL selection process, emphasising their potential to increase the accuracy of selection and reduce data analysis time. The findings of this article provide valuable insights for researchers and practitioners in the oil and gas industry, as well as for those interested in the development of AL selection methods

Feature selection using information gain for improved structural-based alert correlation

Grouping and clustering alerts for intrusion detection based on the similarity of features is referred to as structurally base alert correlation and can discover a list of attack steps. Previous researchers selected different features and data sources manually based on their knowledge and experience, which lead to the less accurate identification of attack steps and inconsistent performance of clustering accuracy. Furthermore, the existing alert correlation systems deal with a huge amount of data that contains null values, incomplete information, and irrelevant features causing the analysis of the alerts to be tedious, time-consuming and error-prone. Therefore, this paper focuses on selecting accurate and significant features of alerts that are appropriate to represent the attack steps, thus, enhancing the structural-based alert correlation model. A two-tier feature selection method is proposed to obtain the significant features. The first tier aims at ranking the subset of features based on high information gain entropy in decreasing order. The second tier extends additional features with a better discriminative ability than the initially ranked features. Performance analysis results show the significance of the selected features in terms of the clustering accuracy using 2000 DARPA intrusion detection scenario-specific dataset

A summary of artificial lift failure, remedies and run life improvements in conventional and unconventional wells.

Artificial lift (AL) systems are crucial for enhancing oil and gas production from reservoirs. However, the failure of these systems can lead to significant losses in production and revenue. This paper explores the different types of AL failures and the causes behind them. The article discusses the traditional methods of identifying and mitigating these failures and highlights the need for new designs and technologies to improve the run life of AL systems. Advances in AL system design and materials, as well as new methods for monitoring and predicting failures using data analytics and machine learning techniques, have been discussed. The findings of this work provide valuable insights for researchers and practitioners in the development of more reliable and efficient AL systems

A UV-Spectrophotmetric Chemometric Method for the Simultaneous Determination of Sulfadoxine and Pyrimethamine in Tablets

In the present study, a simple, inexpensive, precise and accurate uv-spectrophotometric method based on chemometrics, has been developed for the simultaneous determination of sulfadoxine and pyrimethamine in tablet formulation. The % recoveries obtained were 99.7% ± 0.9 and 101.5% ± 0.8 for sulfadoxine and pyrimethamine, respectively. The developed method has been compared to USP-HPLC method with regard to accuracy and precision. The calculated F-ratio and the (t) statistics indicate that there is no significant difference at 5% level with regard to precision and accuracy between the proposed and the USP methods. Moreover, the developed method is simple, cost-effective, and less time-consuming. Accordingly, it can be used advantageously in routine quality control of sulfadoxine and pyrimethamine in tablet formulation

Prediction Model for Construction Cost and Duration in Jordan

Risk is mitigated in the course of reliable prediction. A probabilistic model is proposed to predict the risk effects on time and cost of construction projects. Project managers and consultants can use the model in estimating project cost and duration based on historic data. Statistical regression models and sample tests are developed using real data of 140 projects. The research objective is to develop a model to predict project cost and duration based on historic data of similar projects. The model result can be used by project managers in the planning phase to validate the schedule critical path time and project budget. Research methodology is steered per the following progression: i) Conduct nonparametric test for project cost and time performance. ii) Develop generic multiple-regression models to predict project cost and duration using historic performance data. iii) The percent prediction error is statistically analyzed; and found to be substantial; thus, iv) Custom multiple regression models are developed for each project type to obtain statistically reliable results. In conclusion, the 95% point estimation of error margin= ±0.035%. Therefore, at a probability of 95%, the proposed model predicts the project cost and duration with a precision of ±0.035% of the mean cost and time

Improving the Smart Cities Traffic Management Systems using VANETs and IoT Features

This paper discusses the creation of an integrated worldwide system based on integrating and linking automobiles with VANET, IoT, and AI technologies, which will have a substantial impact on the smart, safe transportation system. This paper aims to apply a proposed project to a specific area in Jordan to examine the projects viability and its impact on reducing the accident rate by controlling traffic with special traffic rules in the study area using a cloud database that stores all the private information for each car and receives information about the cars speed as it travels. When a driver exceeds the speed established by the Traffic Department, he receives warning messages informing him that he has over the speed limit, and if he does not respond to the warning messages, he gets a fine. The research focuses on optimizing the utilization of VANET network services, which is crucial for enhancing public safety applications involving data exchange between automobiles and RSUs. The simulation was conducted using OMNeT++ version 5.7 on Debian 11, Linux 5, and GNOME 3 operating systems. As a network simulator, it is a scientifically approved open-source too

Productivity Improvement of Pre-cast Concrete Installation

The production process of pre-cast concrete installation is analyzed to investigate possible ways for onsite productivity improvement. Although manufactured construction enjoys higher quality and productivity, it is observed that it suffers delays compared to site built construction. Delay causes and respective severity are analyzed for improvement. Firstly, the production process is investigated using the production delay model. Forty cycle data are used in the analysis. The comparative impact and severity are measured for five delay causes, namely: labor, environmental, management, equipment and material on overall system productivity. It is found via the production delay analysis that material, followed by equipment availability then labor were major contributors to system delay. Secondly, statistical analysis on the installation cycle time of three pre-cast component types is carried out, in order to insure whether the delay observed via the first step is attributed to variation of pre-cast pieces. The data used in step one above were not pertinent to product type; therefore, other 90 cycle data are utilized in the statistical analysis, which indicated high variability in cycle time due to product type. Improvement can be achieved through proper scheduling of project equipment and resources. In addition, improvement should target the reduction of installation cycle time variability due to product type

Fermented Camel (Camelus dromedarius) and Bovine Milk Attenuate Azoxymethane-induced Colonic Aberrant Crypt Foci in Fischer 344 Rats

Abstract: Background and Objective: Camel milk is a folk remedy that includes valuable nutrients and bioactive zoochemicals. However, the chemopreventive potential of camel milk against colon carcinogenesis is poorly understood. This study was conducted to investigate the chemopreventive potential of camel (Camelus dromedarius) and bovine milk as well as the impact of fermenting these milks with Lactobacillus acidophilus and Streptococcus thermophilus against early colon carcinogenesis as measured by the reduction of aberrant crypt foci (ACF) in azoxymethane (AOM)-treated Fischer 344 rats. Methodology: Each of 60 weanling male rats was assigned to one of 6 experimental diet groups: Fermented and unfermented camel milk with AOM, fermented and unfermented bovine milk with AOM and positive (PC, AOM only) and negative (NC, saline vehicle only) control groups. The animals were fed the corresponding diets for 3 weeks and then received two subcutaneous injections of AOM or vehicle for 2 consecutive weeks and they were then placed on the corresponding diets for 11 weeks. At termination, all rats were euthanized, colons were harvested and the ACF counts were determined for all tested groups. Immunohistochemical testing was then performed to examine cell proliferation and apoptosis in the camel milk groups. Results: Significant reductions (p<0.05) (48.4-62.1%) in the total ACF count were observed in the colons of the rats fed all milk diets compared with rats fed on PC. However, significant differences were not observed in the total ACF between the camel and bovine milk diets or between the fermented and unfermented milk diets. In addition, significant changes were not observed in the apoptotic index for the camel milk diet compared with the index values for PC and β-catenin was generally localized to the membrane in all examined specimens. Conclusion: By virtue of its bioactive components, camel milk exhibited a chemopreventive potential against early colon carcinogenesis, however, fermentation did not improve its chemopreventive potential