Polycystic ovary syndrome (PCOS) is one of the most common endocrine disorder. To determine the metabolic disorders in women with PCOS, (25) women with PCOS ages (15 - 47) years have been investigated and compared with (20) healthy individuals. All the studied groups were carried out to measure fasting blood sugar, (anti-GAD Ab, anti β-islet cell Ab by IFAT) and measured insulin level by ELISA. There was significant elevation in the concentration of fasting blood sugar than in control groups (p ≤ 0.05) and there was negative results for anti-GAD Ab and anti β-islet cell Ab by IFAT test for serum of women with PCOS, while there was significant differences in the insulin level for women with PCOS compared with control groups (p ≤ 0.05), these indicated that women with PCOS are at high risk for type -2 Diabetes mellitus and reflecting insulin resistance.
In this paper, RBF-based multistage auto-encoders are used to detect IDS attacks. RBF has numerous applications in various actual life settings. The planned technique involves a two-part multistage auto-encoder and RBF. The multistage auto-encoder is applied to select top and sensitive features from input data. The selected features from the multistage auto-encoder is wired as input to the RBF and the RBF is trained to categorize the input data into two labels: attack or no attack. The experiment was realized using MATLAB2018 on a dataset comprising 175,341 case, each of which involves 42 features and is authenticated using 82,332 case. The developed approach here has been applied for the first time, to the knowledge of the authors, to dete
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Cybersecurity refers to the actions that are used by people and companies to protect themselves and their information from cyber threats. Different security methods have been proposed for detecting network abnormal behavior, but some effective attacks are still a major concern in the computer community. Many security gaps, like Denial of Service, spam, phishing, and other types of attacks, are reported daily, and the attack numbers are growing. Intrusion detection is a security protection method that is used to detect and report any abnormal traffic automatically that may affect network security, such as internal attacks, external attacks, and maloperations. This paper proposed an anomaly intrusion detection system method based on a
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Cybersecurity refers to the actions that are used by people and companies to protect themselves and their information from cyber threats. Different security methods have been proposed for detecting network abnormal behavior, but some effective attacks are still a major concern in the computer community. Many security gaps, like Denial of Service, spam, phishing, and other types of attacks, are reported daily, and the attack numbers are growing. Intrusion detection is a security protection method that is used to detect and report any abnormal traffic automatically that may affect network security, such as internal attacks, external attacks, and maloperations. This paper proposed an anomaly intrusion detection system method based on a
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Software-defined networking (SDN) is an innovative network paradigm, offering substantial control of network operation through a network’s architecture. SDN is an ideal platform for implementing projects involving distributed applications, security solutions, and decentralized network administration in a multitenant data center environment due to its programmability. As its usage rapidly expands, network security threats are becoming more frequent, leading SDN security to be of significant concern. Machine-learning (ML) techniques for intrusion detection of DDoS attacks in SDN networks utilize standard datasets and fail to cover all classification aspects, resulting in under-coverage of attack diversity. This paper proposes a hybr
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Thirty uropathogenic E. coli isolates were isolated from hospitalized and non hospitalized patients, complaining of urinary tract infections, of Al-Kadhymia Teaching Hospital and subjected to tRNA extraction. A method of tRNA extraction was modified by adding sodium dodecyl sulfate (SDS) instead of urea. Polyacrylamide gel electrophoresis and two methods of staining, ethidium bromide staining and silver staining, as well as spectrophotometric detection were used.
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Generally, there are many problems that people run into; unemployment is one of these common diseases which usually hits the whole communities leaving crucial effects (economic, social, and psychological) that are difficult to handle them. The current study aims to identify the level of emotional disorders among Iraqi unemployed alumni for the academic years (2013-2016). To this end, the researchers have prepared a questionnaire to measure (anxiety, depression, and anger): these criteria distributed over (30) item. As for sample, it limited to (50) male and female student. The findings of study have revealed that the whole sample showed a high level of emotional disorders, and anger disorder showed higher level than the level of (depress
... Show MoreThe reason for conducting this study is to prolong release of miconazole in the ocular site of action by ocular-based gels (OBGs) formulations. The formulation factors affecting on the release from OBG should be studied using various gelling agents in various concentrations to achieve the improvement in retention and residence time in response to prolonged release. In this study, the formulations were prepared using carbopol 940, pectin, sodium alginate, poloxamer 407, and poly(methacrylic acid) at 0.5%, 1%, and 1.5% w/v, respectively. Hydroxypropyl methylcellulose E5 (HPMC E5) 1% was added as thickening agent/viscosity builder. The formulation containing carbopol 940, pectin and sodium alginate at 1.5% w/v, displayed a noticable im
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