This study aimed to extraction of essential oil from peppermint leaves by using hydro distillation methods. In the peppermint oil extraction with hydro distillation method is studied the effect of the extraction temperature to the yield of peppermint oil. Besides it also studied the kinetics during the extraction process. Then, 2^nd -order mechanism was adopted in the model of hydro distillation for estimation many parameters such as the initial extraction rate, capacity of extraction and the constant rat of extraction with various temperature. The same model was also used to estimate the activation energy. The results showed a spontaneous process, since the  Gibbs free energy had a value negative sign.

    This work has been accomplished through a dense field work on the Sawa Lake. The aim of this work is to highlight on characteristics that are consistent with outstanding universal values to be a new Iraqi site belongs to the World Natural Heritage. This study sorted many unique characteristics might ensure that Sawa Lake as a world natural heritage sites. This study shows that the lake had met four natural criteria of the outstanding universal values: (1) the seventh criterion which states to contain superlative natural phenomena or areas of exceptional natural beauty and aesthetic importance. (2) The eighth criterion which stated to be outstanding example representing major stages of earth's history, including the rec

        The research paper deals with the role of the place making in eco-tourism through a review of international experiences in the eco-tourism industry and its contribution to advancing the reality of tourism there, and attracting the largest number of tourists.  The study is divided into five axes: the first is a study of related concepts, and the second is a study of global experiences, which included three countries: (South Bank (Gabriel's Wharf) - London, Rotterdam in the Netherlands, and dealt with each of Happy Streets and Kendrick Mills, and then the Perak River tourist corridor - Malaysia).  As for the third axis, it is concerned with analyzing these experiences to reach th

The increasing complexity of assaults necessitates the use of innovative intrusion detection systems (IDS) to safeguard critical assets and data. There is a higher risk of cyberattacks like data breaches and unauthorised access since cloud services have been used more frequently. The project's goal is to find out how Artificial Intelligence (AI) could enhance the IDS's ability to identify and classify network traffic and identify anomalous activities. Online dangers could be identified with IDS. An intrusion detection system, or IDS, is required to keep networks secure. We must create efficient IDS for the cloud platform as well, since it is constantly growing and permeating more aspects of our daily life. However, using standard intrusion

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