يشهد المسرح الدولي قضايا مستجدة ومستحدثة مثل تعدد الفاعلين من الدول ومن غير الدول وتزايد مساحات نفوذهم وتأثيرهم ،ومن جانب اخر أثرت جائحة كورونا على البيئة والمناخ بشكل ملموس على جوانب عدة. فضلا عن ذلك تأثرت جميع المجتمعات البشرية بالإرهاب والهجمات الالكترونية وغيرها ومن بينها دول والمجتمع الدولي بإفراده مؤسسات وكيان اقتصادي وسياسي وقانوني وأمني وامتداد اثاره واسبابه الكثيرة والمتداخلة وما يثيره من خلق حا

HM Al-Dabbas, RA Azeez, AE Ali, Iraqi Journal of Science, 2023

Fast economical developments in the US. in second half of nineteenth century contained many social results, such as increasing of stealing and killing crimes and expand of Labor strikes, which resulted in violence actions, and presented acceptable reason for emergence specialist security agencies, first of them "Pinkerton Agency". which played important role in all of that, besides that .. its role in American Civil War such as discovering an attempt to kill elected republican president Abraham Lincoln. This research studied all that aspects, focused on period of 1850 - 1899 of agency's history.

 To expedite the learning process, a group of algorithms known as parallel machine learning algorithmscan be executed simultaneously on several computers or processors. As data grows in both size andcomplexity, and as businesses seek efficient ways to mine that data for insights, algorithms like thesewill become increasingly crucial. Data parallelism, model parallelism, and hybrid techniques are justsome of the methods described in this article for speeding up machine learning algorithms. We alsocover the benefits and threats associated with parallel machine learning, such as data splitting,communication, and scalability. We compare how well various methods perform on a variety ofmachine learning tasks and datasets, and we talk abo

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