Many academics have concentrated on applying machine learning to retrieve information from databases to enable researchers to perform better. A difficult issue in prediction models is the selection of practical strategies that yield satisfactory forecast accuracy. Traditional software testing techniques have been extended to testing machine learning systems; however, they are insufficient for the latter because of the diversity of problems that machine learning systems create. Hence, the proposed methodologies were used to predict flight prices. A variety of artificial intelligence algorithms are used to attain the required, such as Bayesian modeling techniques such as Stochastic Gradient Descent (SGD), Adaptive boosting (ADA), Decision Tre

Botnet detection develops a challenging problem in numerous fields such as order, cybersecurity, law, finance, healthcare, and so on. The botnet signifies the group of co-operated Internet connected devices controlled by cyber criminals for starting co-ordinated attacks and applying various malicious events. While the botnet is seamlessly dynamic with developing counter-measures projected by both network and host-based detection techniques, the convention techniques are failed to attain sufficient safety to botnet threats. Thus, machine learning approaches are established for detecting and classifying botnets for cybersecurity. This article presents a novel dragonfly algorithm with multi-class support vector machines enabled botnet

Many academics have concentrated on applying machine learning to retrieve information from databases to enable researchers to perform better. A difficult issue in prediction models is the selection of practical strategies that yield satisfactory forecast accuracy. Traditional software testing techniques have been extended to testing machine learning systems; however, they are insufficient for the latter because of the diversity of problems that machine learning systems create. Hence, the proposed methodologies were used to predict flight prices. A variety of artificial intelligence algorithms are used to attain the required, such as Bayesian modeling techniques such as Stochastic Gradient Descent (SGD), Adaptive boosting (ADA), Deci

MH Hamzah, AF Abbas, International Journal of Early Childhood Special Education, 2022

This  paper represent  the second  step  i n  a molecular clon i ng program ai ming to clone large DNA  fi·agmen ts of the sal t tolerant  bermudagrass (Cyrwdon  dactylon  L.)  DNA  usi ng  the  bacteriophage  (EM13L3) as    a vector.

In th is  work, a yield of about  I 00  g bacteriophage  DNA  per one  liter culture.was obtained  with.a  purity ranging between (1.7-1.8). The vector JJNA  v.as  completely   double   digested   with  the  restriction   enzymes llamHI   and  EcoRI,  followed  by  pu

Background: intestinal anastomosis is one of the most commonly performed procedures it required to reestablish gastrointestinal continuity after surgical resection, traumatic disruption or bypass procedures. In last decade, advances in intestinal stapling devices have led to an increased frequency of stapled anastomosis. There are varieties of proposed benefit from a stapled technique: better blood supply, reduced tissue manipulation, less edema, uniformity of suture, adequate or perhaps wider lumen at the site of anastomosis, ease and rapidity.
Patient and methods: a prospective study was conducted on 103 patients who suffered from benign and malignant diseases in addition to trauma patients. They were d

Geographic Information Systems (GIS) are obtaining a significant role in handling strategic applications in which data are organized as records of multiple layers in a database. Furthermore, GIS provide multi-functions like data collection, analysis, and presentation. Geographic information systems have assured their competence in diverse fields of study via handling various problems for numerous applications. However, handling a large volume of data in the GIS remains an important issue. The biggest obstacle is designing a spatial decision-making framework focused on GIS that manages a broad range of specific data to achieve the right performance. It is very useful to support decision-makers by providing GIS-based decision support syste

      The Arabic Language is the native tongue of more than 400 million people around the world,  it is also a language that carries an important religious and international weight.  The Arabic language has taken its share of the huge technological explosion that has swept the world, and therefore it needs to be addressed with natural language processing applications and tasks.

This paper aims to survey and gather the most recent research related to Arabic Part of Speech (APoS), pointing to tagger methods used for the Arabic language, which ought to aim to constructing corpus for Arabic tongue. Many AI investigators and researchers have worked and performed POS utilizing various machine-learning methods, such as Hidden-Mark