SCADA is the technology that allows the operator to gather data from one or more various facilities and to send control instructions to those facilities.  This paper represents an adaptable and low cost SCADA system for a particular sugar manufacturing process, by using Programmable Logic Controls (Siemens s7-1200, 1214Dc/ Dc/ Rly). The system will control and monitor the laboratory production line chose from sugar industry. The project comprises of two sections the first one is the hardware section that has been designed, and built using components suitable for making it for laboratory purposes, and the second section was the software as the PLC programming, designing the HMI, creating alarms and trending system. The system will ha

Sixty-four isolate were klebsiella pneumoniae. Fourteen bacteria isolates “Kelbsiella species” were taken from soil and water hospital in the period between October to December 2018, those isolated were cultured on a blood agar to test their ability to hydrolytic due to formation the inhibition zone . Twenty one isolates of K. pneumoniae were selected to be cultured in mineral salt agarfor testing their efficiency to produce laccase enzyme .The efficient isolate was diagnosed depending on phenotypic, microscopic and biochemical tests to be Klebsiella pneumoniae K7. Laccases (benzenediol: oxygen oxidoreductases; EC: 1.10.3.2) are subfamily of multicopper oxidases (MCOs) from Klebsiellapneumoniae K7 has been partially characterized by

This article will address autoclave design considerations and
manufacturing working with high pressure low temperature
supercritical drying technique to produce silica aerogel. The design
elects carbon dioxide as a supercritical fluid (31.7 oC and 72.3 bar).
Both temperature and pressure have independently controlling
facility through present design. The autoclave was light weight (4.5
kg) and factory-made from stainless steel. It contains a high pressure
window for monitoring both transfer carbon dioxide gas to liquid
carbon dioxide and watching supercritical drying via aerogel
preparation process. In this work aerogel samples were prepared and
the true apparent densities, total pore volume and pore size

Siderophores are low molecular weight organic compounds produced by microorganisms growing under low iron concentration.In this study we describe the detection, production and extraction of siderophores secreted by Acinetobacter baumannii (Multiple-drug resistant ) pathogens. One hundered twenty Gram –negative non lactose fermenter bacilli isolates have been collected from three hospitals at Baghdad city over three months. Primary identification of these isolates is performed by standard diagnostic methods (biochemical tests and API 20 NE); 19 clinical isolates of A. baumannii are cultured on CHROMagar (highly selective medium for detection of MDR Acinetobacter) as well as diagnoses is documented by using Vitek 2 system. Isolates are exa

This study proposed a biometric-based digital signature scheme proposed for facial recognition. The scheme is designed and built to verify the person’s identity during a registration process and retrieve their public and private keys stored in the database. The RSA algorithm has been used as asymmetric encryption method to encrypt hashes generated for digital documents. It uses the hash function (SHA-256) to generate digital signatures. In this study, local binary patterns histograms (LBPH) were used for facial recognition. The facial recognition method was evaluated on ORL faces retrieved from the database of Cambridge University. From the analysis, the LBPH algorithm achieved 97.5% accuracy; the real-time testing was done on thirty subj

The convolutional neural networks (CNN) are among the most utilized neural networks in various applications, including deep learning. In recent years, the continuing extension of CNN into increasingly complicated domains has made its training process more difficult. Thus, researchers adopted optimized hybrid algorithms to address this problem. In this work, a novel chaotic black hole algorithm-based approach was created for the training of CNN to optimize its performance via avoidance of entrapment in the local minima. The logistic chaotic map was used to initialize the population instead of using the uniform distribution. The proposed training algorithm was developed based on a specific benchmark problem for optical character recog

Its well known that understanding human facial expressions is a key component in understanding emotions and finds broad applications in the field of human-computer interaction (HCI), has been a long-standing issue. In this paper, we shed light on the utilisation of a deep convolutional neural network (DCNN) for facial emotion recognition from videos using the TensorFlow machine-learning library from Google. This work was applied to ten emotions from the Amsterdam Dynamic Facial Expression Set-Bath Intensity Variations (ADFES-BIV) dataset and tested using two datasets.