Eichhornia crassipes (Mart.) Solms or Water hyacinth is a fertile floating aquatic widespread in worldwide. The form of plants and the anatomy parts of this plant were studied. The most important feature was obvious the air chamber with intercellular spaces by amazing arrangement. As well can notice aerenchyma tissue allow the parts of plants floated on the surface of water located in the ground meristem of root, petiole and in the mesophyll of leaves also presence of two type of crystals raphides and styloid crystals was noted of various member in the plant in addition appear astrosclereids around the air chambers, to support the plant parts from the unsuitable environmental conditions such as the speed of water flow or floods or high leve

Methods: 112 placentae samples were investigated during the period from August 2007 to August 2008 under light microscopefor mother aged 15 - 45 years old.Results: It was found that normal placental shapes had no correlation to mother age, while abnormal shapes were found more inyoung age groups. The better placental measured parameters were found in mother age 20-24 years. The percentages ofabnormal umbilical cord insertion were very high compared to other studies. Babies’ gender had a correlation with theplacental thickness; male babies have thicker placentae than females. Male babies have longer umbilical cords with widerdiameter than females. Light microscope picture showed the chorionic villi with isolated fetal blood vessel were hig

SM ADAI, BN RASHID, Journal of Current Researches on Social Sciences, 2023

Corruption (Definition , Characteristics , Reasons , Features , and ways of combating it)

Researchers employ behavior based malware detection models that depend on API tracking and analyzing features to identify suspected PE applications. Those malware behavior models become more efficient than the signature based malware detection systems for detecting unknown malwares. This is because a simple polymorphic or metamorphic malware can defeat signature based detection systems easily. The growing number of computer malwares and the detection of malware have been the concern for security researchers for a large period of time. The use of logic formulae to model the malware behaviors is one of the most encouraging recent developments in malware research, which provides alternatives to classic virus detection methods. To address the l

In modern technology, the ownership of electronic data is the key to securing their privacy and identity from any trace or interference. Therefore, a new identity management system called Digital Identity Management, implemented throughout recent years, acts as a holder of the identity data to maintain the holder’s privacy and prevent identity theft. Therefore, an overwhelming number of users have two major problems, users who own data and third-party applications will handle it, and users who have no ownership of their data. Maintaining these identities will be a challenge these days. This paper proposes a system that solves the problem using blockchain technology for Digital Identity Management systems. Blockchain is a powerful techniqu

With the rapid development of computers and network technologies, the security of information in the internet becomes compromise and many threats may affect the integrity of such information. Many researches are focused theirs works on providing solution to this threat. Machine learning and data mining are widely used in anomaly-detection schemes to decide whether or not a malicious activity is taking place on a network. In this paper a hierarchical classification for anomaly based intrusion detection system is proposed. Two levels of features selection and classification are used. In the first level, the global feature vector for detection the basic attacks (DoS, U2R, R2L and Probe) is selected. In the second level, four local feature vect