Aleppo bentonite was investigated to remove ciprofloxacin hydrochloride from aqueous solution. Batch adsorption experiments were conducted to study the several factors affecting the removal process, including contact time, pH of solution, bentonite dosage, ion strength, and temperature. The optimum contact time, pH of solution and bentonite dosage were determined to be 60 minutes, 6 and 0.15 g/50 ml, respectively. The bentonite efficiency in removing CIP decreased from 89.9% to 53.21% with increasing Ionic strength from 0 to 500mM, and it increased from 89% to 96.9% when the temperature increased from 298 to 318 K. Kinetic studies showed that the pseudo second-order model was the best in describing  the adsorption sys

The field of Optical Character Recognition (OCR) is the process of converting an image of text into a machine-readable text format. The classification of Arabic manuscripts in general is part of this field. In recent years, the processing of Arabian image databases by deep learning architectures has experienced a remarkable development. However, this remains insufficient to satisfy the enormous wealth of Arabic manuscripts. In this research, a deep learning architecture is used to address the issue of classifying Arabic letters written by hand. The method based on a convolutional neural network (CNN) architecture as a self-extractor and classifier. Considering the nature of the dataset images (binary images), the contours of the alphabet

Offline handwritten signature is a type of behavioral biometric-based on an image. Its problem is the accuracy of the verification because once an individual signs, he/she seldom signs the same signature. This is referred to as intra-user variability. This research aims to improve the recognition accuracy of the offline signature. The proposed method is presented by using both signature length normalization and histogram orientation gradient (HOG) for the reason of accuracy improving. In terms of verification, a deep-learning technique using a convolution neural network (CNN) is exploited for building the reference model for a future prediction. Experiments are conducted by utilizing 4,000 genuine as well as 2,000 skilled forged signatu

Nonlinear time series analysis is one of the most complex problems ; especially the nonlinear autoregressive with exogenous variable (NARX) .Then ; the problem of model identification and the correct orders determination considered the most important problem in the analysis of time series . In this paper , we proposed splines  estimation method for model identification , then we used three criterions for the correct orders determination. Where ; proposed method used to estimate the additive splines for model identification , And the rank determination depends on the additive property  to avoid the problem of curse dimensionally . The proposed method is one of the nonparametric methods , and the simulation results give a

Secure storage of confidential medical information is critical to healthcare organizations seeking to protect patient's privacy and comply with regulatory requirements. This paper presents a new scheme for secure storage of medical data using Chaskey cryptography and blockchain technology. The system uses Chaskey encryption to ensure integrity and confidentiality of medical data, blockchain technology to provide a scalable and decentralized storage solution. The system also uses Bflow segmentation and vertical segmentation technologies to enhance scalability and manage the stored data. In addition, the system uses smart contracts to enforce access control policies and other security measures. The description of the system detailing and p

Abstract 

     This research aims to analyze the reality of the production process in an assembly line Cars (RUNNA) in the public company for the automotive industry / Alexandria through the use of some Lean production tools, and data were collected through permanence in the company to identify the problems of the line in order to find appropriate to adopt some Lean production tools solutions, and results showed the presence of Lead time in some stations, which is reflected on the customer's waiting time to get the car, as well as some of the problems existing in the car produced such as high temperature of the car, as the company does not take into account customer preferences,

Teen-Computer Interaction (TeenCI) stands in an infant phase and emerging in positive path. Compared to Human-Computer Interaction (generally dedicated to adult) and Child-Computer Interaction, TeenCI gets less interest in terms of research efforts and publications. This has revealed extensive prospects for researchers to explore and contribute in the region of computer design and evaluation for teen, in specific. As a subclass of HCI and a complementary for CCI, TeenCI that tolerates teen group, should be taken significant concern in the sense of its context, nature, development, characteristics and architecture. This paper tends to discover teen’s emotion contribution as the first attempt towards building a conceptual model for TeenC

Solar cells has been assembly with electrolytes including I−/I−3 redox duality employ polyacrylonitrile (PAN), ethylene carbonate (EC), propylene carbonate (PC), with double iodide salts of tetrabutylammonium iodide (TBAI) and Lithium iodide (LiI) and iodine (I2) were thoughtful for enhancing the efficiency of the solar cells. The rendering of the solar cells has been examining by alteration the weight ratio of the salts in the electrolyte. The solar cell with electrolyte comprises (60% wt. TBAI/40% wt. LiI (+I2)) display elevated efficiency of 5.189% under 1000 W/m2 light intensity. While the solar cell with electrolyte comprises (60% wt. LiI/40% wt. TBAI (+I2)) display a lower efficiency of 3.189%. The conductivity raises with the