ABSTRACT: Oxadiazole ring is a heterocyclic molecule with an oxygen and two nitrogen atoms spread throughout its five-membered structure. There are four different isomers that have been discovered, Because of their wide applications in a range of sectors, including medications . Some of these biological activity are; anticonvulsant capacity, anticancer as well, antibacterial, antiviral, antifungal,  antimalarial, antitubercular, anti-asthmatic, antidepressant, antidiabetic, antioxidant, antiparkinsonian, analgesic and  anti-inflammatory, are just some of the therapeutic uses that have drawn attention to drug candidates containing an oxadiazole moiety. This review, we will examine the various methods of oxadiazole synthesis. The mo

Historically, medicinal herbs have been utilized as an important origin of chemicals with particular therapeutic potentials, and they continue to be a great place to find new medication candidates. Parthenocissus quinquefolia L. is a member of the grape-growing family Vitaceae. It is indigenous to Central and North America. It is widely dispersed in Iraqi gardens and plant houses from north to south. Traditionally, it has many uses, like relieving constipation, treating jaundice, expectorant, emetic, and others. At the same time, its proven activities include antioxidant activity, antimicrobial, anti-diabetic, thrombin inhibitor effect, and medicine for treating eyelid eczema. Parthenocissus quinquefolia contains valuable phytochemicals lik

Confocal microscope imaging has become popular in biotechnology labs. Confocal imaging technology utilizes fluorescence optics, where laser light is focused onto a specific spot at a defined depth in the sample. A considerable number of images are produced regularly during the process of research. These images require methods of unbiased quantification to have meaningful analyses. Increasing efforts to tie reimbursement to outcomes will likely increase the need for objective data in analyzing confocal microscope images in the coming years. Utilizing visual quantification methods to quantify confocal images with naked human eyes is an essential but often underreported outcome measure due to the time required for manual counting and e

Banks face many of the various risks: which are of dangerous phenomena that cause the state achieved a waste of money and a threat to future development plans to be applied to reach the goals set by: prompting banks and departments to find appropriate solutions and fast: and it was within these solutions rely on Banking risk management and effective role in defining and identifying: measuring and monitoring risk and trying to control and take risks is expected to occur in order to encircle and make it in within acceptable limits: and try to avoid them in the future to reduce the losses that are likely to be exposed to the bank: and it began to emerge and dominate a lot of legislation that seeks to structure the year risk management and t

Shadow removal is crucial for robot and machine vision as the accuracy of object detection is greatly influenced by the uncertainty and ambiguity of the visual scene. In this paper, we introduce a new algorithm for shadow detection and removal based on different shapes, orientations, and spatial extents of Gaussian equations. Here, the contrast information of the visual scene is utilized for shadow detection and removal through five consecutive processing stages. In the first stage, contrast filtering is performed to obtain the contrast information of the image. The second stage involves a normalization process that suppresses noise and generates a balanced intensity at a specific position compared to the neighboring intensit

Support vector machine (SVM) is a popular supervised learning algorithm based on margin maximization. It has a high training cost and does not scale well to a large number of data points. We propose a multiresolution algorithm MRH-SVM that trains SVM on a hierarchical data aggregation structure, which also serves as a common data input to other learning algorithms. The proposed algorithm learns SVM models using high-level data aggregates and only visits data aggregates at more detailed levels where support vectors reside. In addition to performance improvements, the algorithm has advantages such as the ability to handle data streams and datasets with imbalanced classes. Experimental results show significant performance improvements in compa

Administrative procedures in various organizations produce numerous crucial records and data. These
records and data are also used in other processes like customer relationship management and accounting
operations.It is incredibly challenging to use and extract valuable and meaningful information from these data
and records because they are frequently enormous and continuously growing in size and complexity.Data
mining is the act of sorting through large data sets to find patterns and relationships that might aid in the data
analysis process of resolving business issues. Using data mining techniques, enterprises can forecast future
trends and make better business decisions.The Apriori algorithm has bee