In this paper, a fast lossless image compression method is introduced for compressing medical images, it is based on splitting the image blocks according to its nature along with using the polynomial approximation to decompose image signal followed by applying run length coding on the residue part of the image, which represents the error caused by applying polynomial approximation. Then, Huffman coding is applied as a last stage to encode the polynomial coefficients and run length coding. The test results indicate that the suggested method can lead to promising performance.

                The research aims to explain the role of huge data analyzes in measuring quality costs in the Iraqi company for the production of seed, and the research problem was diagnosed with the weakness of the approved method to measure quality costs, and the weak traditional systems of data analyzes, the researcher in the theoretical aspect relied on collecting sources and previous studies, as well as Adoption of the applied analytical approach in the practical aspect, as a set of financial analyzes were applied within the measurement of quality costs and a statement of the role of data analyzes in the practical side, the research concluded to a set of conc

Most heuristic search method's performances are dependent on parameter choices. These parameter settings govern how new candidate solutions are generated and then applied by the algorithm. They essentially play a key role in determining the quality of the solution obtained and the efficiency of the search. Their fine-tuning techniques are still an on-going research area. Differential Evolution (DE) algorithm is a very powerful optimization method and has become popular in many fields. Based on the prolonged research work on DE, it is now arguably one of the most outstanding stochastic optimization algorithms for real-parameter optimization. One reason for its popularity is its widely appreciated property of having only a small number of par

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.

The Internet is providing vital communications between millions of individuals. It is also more and more utilized as one of the commerce tools; thus, security is of high importance for securing communications and protecting vital information. Cryptography algorithms are essential in the field of security. Brute force attacks are the major Data Encryption Standard attacks. This is the main reason that warranted the need to use the improved structure of the Data Encryption Standard algorithm. This paper proposes a new, improved structure for Data Encryption Standard to make it secure and immune to attacks. The improved structure of Data Encryption Standard was accomplished using standard Data Encryption Standard with a new way of two key gene

تناول المقال موضوع استثمار الذكاء الاصطناعي في تحليل البيانات الضخمة داخل المؤسسات العلمية، وركز على توضيح أهمية هذا التكامل في تعزيز الأداء الأكاديمي والبحثي. استعرضت المقالة تعريفات كل من الذكاء الاصطناعي والبيانات الضخمة، وأنواع البيانات داخل المؤسسات العلمية، ثم بينت أبرز التطبيقات العملية مثل التنبؤ بأداء الطلبة، والإرشاد الذكي، وتحليل سلوك المستخدمين، والفهرسة التلقائية. كما ناقشت المقالة التحدي

This paper  deals  to how to estimate points non measured spatial data when the number of its terms (sample spatial) a few, that are not preferred for the estimation process, because we also know that whenever if the data is large, the estimation results of the points non measured to be better and thus the variance estimate less, so the idea of this paper is how to take advantage of the data other secondary (auxiliary), which have a strong correlation with the primary data (basic) to be estimated single points of non-measured, as well as measuring the variance estimate, has been the use of technique Co-kriging in this field to build predictions spatial estimation process, and then we applied this idea to real data in th