New Schiff base, namely [2-(carboxy methylene-amino)-phenyl imino] acetic acid (L) and its some metal complexes [LCo.2H2O], [LNi.2H2O], [LCu].3H2O, [LCd.2H2O], [LHg.2H2O] and [LPb.2H2O], were reported and characterized by elemental analysis, metal content, spectroscopic methods, magnetic moments and conductivity measurements, it is found that the geometrical structures of these complexes are octahedral [Co(II), Ni(II), Cd(II), Hg(II), Pb(II) and square planar Cu(II).The complexes have been found to posses 1:1 (M:L) stoichiometry

 Automatic recognition of individuals is very important in modern eras. Biometric techniques have emerged as an answer to the matter of automatic individual recognition. This paper tends to give a technique to detect pupil which is a mixture of easy morphological operations and Hough Transform (HT) is presented in this paper. The circular area of the eye and pupil is divided by the morphological filter as well as the Hough Transform (HT) where the local Iris area has been converted into a rectangular block for the purpose of calculating inconsistencies in the image. This method is implemented and tested on the Chinese Academy of Sciences (CASIA V4) iris image database 249 person and the IIT Delhi (IITD) iris

   Regarding to the computer system security, the intrusion detection systems are fundamental components for discriminating attacks at the early stage. They monitor and analyze network traffics, looking for abnormal behaviors or attack signatures to detect intrusions in early time. However, many challenges arise while developing flexible and efficient network intrusion detection system (NIDS) for unforeseen attacks with high detection rate. In this paper, deep neural network (DNN) approach was proposed for anomaly detection NIDS. Dropout is the regularized technique used with DNN model to reduce the overfitting. The experimental results applied on NSL_KDD dataset. SoftMax output layer has been used with cross entropy loss funct

Convolutional Neural Networks (CNN) have high performance in the fields of object recognition and classification. The strength of CNNs comes from the fact that they are able to extract information from raw-pixel content and learn features automatically. Feature extraction and classification algorithms can be either hand-crafted or Deep Learning (DL) based. DL detection approaches can be either two stages (region proposal approaches) detector or a single stage (non-region proposal approach) detector. Region proposal-based techniques include R-CNN, Fast RCNN, and Faster RCNN. Non-region proposal-based techniques include Single Shot Detector (SSD) and You Only Look Once (YOLO). We are going to compare the speed and accuracy of Faster RCNN,

            A spectrophotometric- reverse flow injection analysis (rFIA) method has been proposed for the   determination of Nitrazepam (NIT) in pure and pharmaceutical preparations. The method is based upon the coupling reaction of NIT with a new reagent O-Coumaric acid (OCA) in the presence of sodium periodate in an aqueous solution. The blue color product was measured at 632 nm. The variation (chemical and physical parameters) related with reverse flow system were estimated. The linearity was over the range 15 - 450 µg/mL of NIT with detection limits and limit of quantification of 3.425 and 11.417 µg mL^-1 NIT,respectively. The sample throughput of 28 samples