With the proliferation of both Internet access and data traffic, recent breaches have brought into sharp focus the need for Network Intrusion Detection Systems (NIDS) to protect networks from more complex cyberattacks. To differentiate between normal network processes and possible attacks, Intrusion Detection Systems (IDS) often employ pattern recognition and data mining techniques. Network and host system intrusions, assaults, and policy violations can be automatically detected and classified by an Intrusion Detection System (IDS). Using Python Scikit-Learn the results of this study show that Machine Learning (ML) techniques like Decision Tree (DT), Naïve Bayes (NB), and K-Nearest Neighbor (KNN) can enhance the effectiveness of an Intrusi

Crop yield prediction is a critical measurement, especially in the time when parts of the world are suffering from farming issues. Yield forecasting gives an alert regarding economic trading, food production monitoring, and global food security. This research was conducted to investigate whether active optical sensors could be utilized for potato (Solanum tuberosum L.) yield prediction at the mid.le of the growing season. Three potato cultivars (Russet Burbank, Superior, and Shepody) were planted and six rates of N (0, 56, 112, 168, 224, and 280 kg ha−1), ammonium sulfate, which was replaced by ammonium nitrate in the 2nd year, were applied on 11 sites in a randomized complete block design, with four replications. Normalized difference ve

Abstract 

     The aim of this work is to create a power control system for wind turbines based on fuzzy logic. Three power control loop was considered including: changing the pitch angle of  the blade, changing the length of the blade and turning the nacelle. The stochastic law was given for changes and instant inaccurate assessment of wind conditions changes. Two different algorithms were used for fuzzy inference in the control loop, the Mamdani and Larsen algorithms. These two different algorithms are materialized and developed in this study in Matlab-Fuzzy logic toolbox which has been practically implemented using necessary intelligent control system in electrical engineerin

A field experiment is conducted to study the effect of different levels of peat (0, 25, 50, 75, and 100 Mg ha-1 to uncropped and cropped soil to wheat. Soil samples are taken in different period of time (0, 3, 30, 60, 90, 120, and 180 days after cultivation to determine (NaHCO3-Exteractable P at 3 different depths (0-10, 10-20, and 20-30 cm). Field Experiment is conducted in a randomized complete block design (RCBD) with four replicates. Wheat, Al-Rasheed variety, is cultivated as a testing crop. The entire field is equally dived in two divisions. One of the two divisions is cultivated to wheat and the second is left uncropped. The effect of five levels of peat namely 0, 25, 50, 75, 100 Mg ha-1 is investigated. Soils are fully analyzed

The most important environmental constraints at the present time
is the accumulation of glass waste (transparent glass bottles). A lot of
experiments and research have been made on waste and recycling
glass to get use it as much as possible. This research using recycling
of locally waste colorless glass to turn them into raw materials as
alternative of certain percentages of cement to save the environment
from glass waste and reduce some of the disadvantages of cement
with conserving the mechanical and physical properties of concrete
made. A set of required samples were prepared for mechanical test
with different weight percentage of waste glass (2%, 4%, 5%, 6%,
8%, 10%, 15%, 20% and 25%). American standard

Mycobacterium tuberculosis resistance to rifampicin is mainly mediated through mutations in the rpoB gene. The effects of rpoB mutations are relieved by secondary mutations in rpoA or rpoC genes. This study aims to identify mutations in rpoB, rpoA, and rpoC genes of Mycobacterium tuberculosis isolates and clarify their contribution to rifampicin resistance. Seventy isolates were identified by acid-fast bacilli smear, Genexpert assay, and growth on Lowenstein Jensen medium. Drug susceptibility, testing was performed by the proportional method.  DNA extraction, PCR, and sequencing were accomplished for the entire rpoA, rpoB, and

Maximizing the net present value (NPV) of oil field development is heavily dependent on optimizing well placement. The traditional approach entails the use of expert intuition to design well configurations and locations, followed by economic analysis and reservoir simulation to determine the most effective plan. However, this approach often proves inadequate due to the complexity and nonlinearity of reservoirs. In recent years, computational techniques have been developed to optimize well placement by defining decision variables (such as well coordinates), objective functions (such as NPV or cumulative oil production), and constraints. This paper presents a study on the use of genetic algorithms for well placement optimization, a ty

Abstract: Word sense disambiguation (WSD) is a significant field in computational linguistics as it is indispensable for many language understanding applications. Automatic processing of documents is made difficult because of the fact that many of the terms it contain ambiguous. Word Sense Disambiguation (WSD) systems try to solve these ambiguities and find the correct meaning. Genetic algorithms can be active to resolve this problem since they have been effectively applied for many optimization problems. In this paper, genetic algorithms proposed to solve the word sense disambiguation problem that can automatically select the intended meaning of a word in context without any additional resource. The proposed algorithm is evaluated on a col