Abstract: The utility of DNA sequencing in diagnosing and prognosis of diseases is vital for assessing the risk of genetic disorders, particularly for asymptomatic individuals with a genetic predisposition. Such diagnostic approaches are integral in guiding health and lifestyle decisions and preparing families with the necessary foreknowledge to anticipate potential genetic abnormalities. The present study explores implementing a define-by-run deep learning (DL) model optimized using the Tree-structured Parzen estimator algorithm to enhance the precision of genetic diagnostic tools. Unlike conventional models, the define-by-run model bolsters accuracy through dynamic adaptation to data during the learning process and iterative optimization

Abu Firas al- Hamdani is one of the most prominent abbasid poets Who characterized their poetry with high artistic quality especially in his Romyate which blended the quality of feelings of grief, sorrow, longing and nostalgia that makes sensitive self conflict that stems with time from one hand and with place on the other hand. Because we are dealing with a poet lived west spatial coercive which it has been hurt him within a time conflict swinging between despair and some times patience and hope other times between the present and his painful reality also between the past and the beautiful times.
This researcher is to stand on this Romyat by monitoring effectiveness of the poetic text based on conflict between the presenc

  eroticism formed a basic focus in contemporary studies and caused a problematic clash in terms of terminology, as some interpreted it by pornography and another interpreted it as aesthetic, so this research came to seek to decipher this terminological clash, and to be known as erotech in terms of cognitive significance, Accordingly, the research culminated in four chapters. The first chapter (Methodological Framework) talks about the research problem that came according to the following question: “How is the erotic act built in the theatrical text and what are the epistemic connotations that express its subjectivity? Then followed by the importance of research and the need for it, then the objective of the research, and the boun

Compression is the reduction in size of data in order to save space or transmission time. For data transmission, compression can be performed on just the data content or on the entire transmission unit (including header data) depending on a number of factors. In this study, we considered the application of an audio compression method by using text coding where audio compression represented via convert audio file to text file for reducing the time to data transfer by communication channel. Approach: we proposed two coding methods are applied to optimizing the solution by using CFG. Results: we test our application by using 4-bit coding algorithm the results of this method show not satisfy then we proposed a new approach to compress audio fil

Features is the description of the image contents which could be corner, blob or edge. Corners are one of the most important feature to describe image, therefore there are many algorithms to detect corners such as Harris, FAST, SUSAN, etc. Harris is a method for corner detection and it is an efficient and accurate feature detection method. Harris corner detection is rotation invariant but it isn’t scale invariant. This paper presents an efficient harris corner detector invariant to scale, this improvement done by using gaussian function with different scales. The experimental results illustrate that it is very useful to use Gaussian linear equation to deal with harris weakness.

Association rules mining (ARM) is a fundamental and widely used data mining technique to achieve useful information about data. The traditional ARM algorithms are degrading computation efficiency by mining too many association rules which are not appropriate for a given user. Recent research in (ARM) is investigating the use of metaheuristic algorithms which are looking for only a subset of high-quality rules. In this paper, a modified discrete cuckoo search algorithm for association rules mining DCS-ARM is proposed for this purpose. The effectiveness of our algorithm is tested against a set of well-known transactional databases. Results indicate that the proposed algorithm outperforms the existing metaheuristic methods.