The water quality index is the most common mathematical way of monitoring water characteristics due to the reasons for the water parameters to identify the type of water and the validity of its use, whether for drinking, agricultural, or industrial purposes. The water arithmetic indicator method was used to evaluate the drinking water of the Al-Muthana project, where the design capacity was (40000) m3/day, and it consists of traditional units used to treat raw water. Based on the water parameters (Turb, TDS, TH, SO4, NO2, NO3, Cl, Mg, and Ca), the evaluation results were that the quality of drinking water is within the second category of the requirements of the WHO (86.658%) and the first category of the standard has not

String matching is seen as one of the essential problems in computer science. A variety of computer applications provide the string matching service for their end users. The remarkable boost in the number of data that is created and kept by modern computational devices influences researchers to obtain even more powerful methods for coping with this problem. In this research, the Quick Search string matching algorithm are adopted to be implemented under the multi-core environment using OpenMP directive which can be employed to reduce the overall execution time of the program. English text, Proteins and DNA data types are utilized to examine the effect of parallelization and implementation of Quick Search string matching algorithm on multi-co

Early diagnosis and clinical decision-making depend on accurate brain tumor classification using magnetic resonance imaging (MRI). However, traditional deep learning methods usually rely on centralized medical data, which raises privacy concerns and limits the use of distributed clinical data. This research proposes a privacy-preserving federated learning framework for MRI image-based binary brain tumor classification using a decentralized ResNet-18 architecture that enables collaborative training without sharing raw patient data. To reflect realistic clinical conditions, the framework integrates heterogeneous multi-source datasets in different image formats (PNG and JPG) and evaluates performance under both IID and non-IID settings

Steganography is defined as hiding confidential information in some other chosen media without leaving any clear evidence of changing the media's features. Most traditional hiding methods hide the message directly in the covered media like (text, image, audio, and video). Some hiding techniques leave a negative effect on the cover image, so sometimes the change in the carrier medium can be detected by human and machine. The purpose of suggesting hiding information is to make this change undetectable. The current research focuses on using complex method to prevent the detection of hiding information by human and machine based on spiral search method, the Structural Similarity Index Metrics measures are used to get the accuracy and quality

Decision-making in Operations Research is the main point in various studies in our real-life applications. However, these different studies focus on this topic. One drawback some of their studies are restricted and have not addressed the nature of values in terms of imprecise data (ID). This paper thus deals with two contributions. First, decreasing the total costs by classifying subsets of costs. Second, improving the optimality solution by the Hungarian assignment approach. This newly proposed method is called fuzzy sub-Triangular form (FS-TF) under ID. The results obtained are exquisite as compared with previous methods including, robust ranking technique, arithmetic operations, magnitude ranking method and centroid ranking method. This

This study suggests using the recycled plastic waste to prepare the polymer matrix composite (PMCs) to use in different applications. Composite materials were prepared by mixing the polyester resin (UP) with plastic waste, two types of plastic waste were used in this work included polyethylene-terephthalate (PET) and Polyvinyl chloride (PVC) with varies weight fractions (0, 5, 10, 15, 20 and 25 %) added as a filler in flakes form. Charpy impact test was performed on the prepared samples to calculate the values of impact strength (I.S). Flexural and hardness tests were carried out to calculate the values of flexural strength and hardness. Acoustic insulation and optical microscope tests were carried out. In general, it is found that UP/PV

<p>Combating the COVID-19 epidemic has emerged as one of the most promising healthcare the world's challenges have ever seen. COVID-19 cases must be accurately and quickly diagnosed to receive proper medical treatment and limit the pandemic. Imaging approaches for chest radiography have been proven in order to be more successful in detecting coronavirus than the (RT-PCR) approach. Transfer knowledge is more suited to categorize patterns in medical pictures since the number of available medical images is limited. This paper illustrates a convolutional neural network (CNN) and recurrent neural network (RNN) hybrid architecture for the diagnosis of COVID-19 from chest X-rays. The deep transfer methods used were VGG19, DenseNet121

Nowadays power systems are huge networks that consist of electrical energy sources, static and lumped load components, connected over long distances by A.C. transmission lines. Voltage improvement is an important aspect of the power system. If the issue is not dealt with properly, may lead to voltage collapse.  In this paper, HVDC links/bipolar connections were inserted in a power system in order to improve the voltage profile. The load flow was simulated by Electrical Transient Analyzer Program (ETAP.16) program in which Newton- Raphson method is used. The load flow simulation studies show a significant enhancement of the power system performance after applying HVDC links on Kurdistan power systems. Th