Most available methods for unit hydrographs (SUH) derivation involve manual, subjective fitting of
a hydrograph through a few data points. The use of probability distributions for the derivation of synthetic
hydrographs had received much attention because of its similarity with unit hydrograph properties. In this
paper, the use of two flexible probability distributions is presented. For each distribution the unknown
parameters were derived in terms of the time to peak(tp), and the peak discharge(Qp). A simple Matlab
program is prepared for calculating these parameters and their validity was checked using comparison
with field data. Application to field data shows that the gamma and lognormal distributions had fit well.<

The results of the current study showed that the liver of H. javanicus appeared as large lobulated organ divided into six distinct lobes, that filled the cranial region and little extended to the middle region of abdominal cavity. On the other hand, liver of S. carolinensis laid against the diaphragm, occupied the cranial region of the abdominal cavity and consisted of five lobes. The liver is surrounded with a thin capsule of dense regular collagenous connective tissue and few numbers of smooth muscles fibers can be seen in the capsule that covered the squirrel liver. The liver parenchyma divided into a large number of interconnected hepatic lobules marked only by the abundant amount of connective tissue bordered the triads, and within the

(Received 21 May 2019, Revised 30 September 2019, Accepted 21 October 2019)ABSTRACT : The results of the current study showed that the liver of H. javanicus appeared as large lobulated organ dividedinto six distinct lobes, that filled the cranial region and little extended to the middle region of abdominal cavity. On the otherhand, liver of S. carolinensis laid against the diaphragm, occupied the cranial region of the abdominal cavity and consisted of fivelobes. The liver is surrounded with a thin capsule of dense regular collagenous connective tissue and few numbers of smoothmuscles fibers can be seen in the capsule that covered the squirrel liver. The liver parenchyma divided into a large number ofinterconnected hepatic lobules marked

The present study aim at preparing frusemide in liquid form suitable for oral use. This is achieved through preparing different liquid forms of frusemide. The frusemide liquid is prepared in the following forms: oral solution, syrup and elixir with intensity of 1, 0.4 and 0.8% weight /volume respectively and in combination with potassium carbonate, polysorbate 80, alcohol and phosphate buffer solution of pH8 to dissolve the frusemide in the above mentioned forms. The different forms of the prepared medicine have been stored in glass bottles that can provide protection against light and at 40, 50, 60⁰C for four months. Besides the pH has been checked to decide the period of validity. The results show that the expiration date of

In this work, new compounds containing 1,2,4-oxadiazole units were synthesized, characterized, and their crystalline liquid qualities were also studied. The synthesis of compound [I ] starts with the reaction 4-hydroxybenzonitrile with phthaloyl chloride to yield nitrile compound. Then the later compound reacted with hydroxyl amine hydrochloride to obtain compound [II]. Next, 1,2,4-Oxadiazole compounds [III]a-c and [IV] were obtained by the reaction between compound [II] with various acid chlorides(acetyl chloride, chloroacetyl chloride, benzoyl chloride) and phthaloyl chloride in pyridine, respectively. FTIR, 1HNMR and mass spectroscopy were used to analyze the synthesized compounds Spectroscopic investigation verified the synthetic

Statistical learning theory serves as the foundational bedrock of Machine learning (ML), which in turn represents the backbone of artificial intelligence, ushering in innovative solutions for real-world challenges. Its origins can be linked to the point where statistics and the field of computing meet, evolving into a distinct scientific discipline. Machine learning can be distinguished by its fundamental branches, encompassing supervised learning, unsupervised learning, semi-supervised learning, and reinforcement learning. Within this tapestry, supervised learning takes center stage, divided in two fundamental forms: classification and regression. Regression is tailored for continuous outcomes, while classification specializes in c

Two unsupervised classifiers for optimum multithreshold are presented; fast Otsu and k-means. The unparametric methods produce an efficient procedure to separate the regions (classes) by select optimum levels, either on the gray levels of image histogram (as Otsu classifier), or on the gray levels of image intensities(as k-mean classifier), which are represent threshold values of the classes. In order to compare between the experimental results of these classifiers, the computation time is recorded and the needed iterations for k-means classifier to converge with optimum classes centers. The variation in the recorded computation time for k-means classifier is discussed.