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Important announcement for final-year students regarding the Egyptian Student Participation Survey (Third Edition)

Important Announcement for Final Year Students Regarding the Egyptian Student Participation Survey (Third Edition)

 Our dear final year students in the Faculty of Computers and Information,

 In line with the university's commitment to developing the educational process and measuring the quality of student participation 

 we would like to inform you that we have begun receiving your responses to the "Egyptian Student Participation Survey - Third Edition 

" Why participate?

 Your opinion is the cornerstone for developing student and educational services in your faculty 

 Survey link: [https://esse.scu.eg] 

Important Notes

 Please log in and fill out the information accurately

 Participation directly contributes to raising the ranking of your faculty and university

 For inquiries, please contact the Student Welfare Department

Wishing you all the best of luck and success

Director of Student Welfare/Hossam El-Din Mostafa

1

 

An Optimized Pattern Matching Algorithm based on Suffix Arrays with LCP-Guided Binary Search: A Time-Efficient Approach for Large-Scale Text Processing

Research Abstract

Pattern matching is a fundamental operation in
computational biology, information retrieval, and text processing.
Despite advances in algorithms, efficiently searching large-scale
texts, particularly genomic sequences spanning billions of base
pairs, remains a significant challenge. Existing approaches face
substantial limitations including Boyer-Moore algorithm’s poor
worst-case performance of O(mn) and limited scalability on large
datasets, KMP algorithm’s high memory overhead and poor
cache locality despite O(m+n) complexity, traditional suffix array
methods’ expensive O(mlogn) search time with costly preprocessing,
and hash-based approaches like Rabin-Karp’s vulnerability
to hash collisions and poor performance on repetitive sequences
common in genomic data.
This paper presents LCP-Optimized Suffix Array (LOSA),
a high-performance pattern matching algorithm that combines
suffix arrays with Longest Common Prefix (LCP) array optimizations
and parallel processing to achieve faster search times
with scalable memory usage. LOSA reduces the worst-case search
complexity from O(m log n) to nearly O(m + log n), where
m length pattern and n length the text. This improvement
is achieved through LCP-aware skips to minimize redundant
comparisons, as well as parallelized construction and query
phases, for modern multicore systems.

Research Authors
Mohmoud K Diab, Taysir Hassan A Soliman, Amr M Mohamed, Ibrahim E Elsemman
Research Date
Research Department
Research Journal
IEEE Xplore
Research Publisher
IEEE
Research Year
2025

A novel in silico molecular tool for comprehensive differentiation of Mycobacterium species

Research Abstract
  • The Identification of various mycobacterial species is critical for understanding their pathogenicity
    and epidemiology. Despite the existence of several established methods for identifying mycobacterial
    species, each of these methods has several significant limitations, including high costs, substantial
    time demands, and a restricted ability to detect a wide range of recoverable species. This study
    presents an in silico method using restriction fragment length polymorphism (RFLP) to differentially
    identify 75 clinically important mycobacterial species.The present investigation employed specific
    primer combinations to identify and generate a distinct hypervariable sequence across the ribosomal
    RNA gene. This unique sequence using appropriate restriction enzyme digestion followed by gel
    electrophoresis enabled the creation of highly precise and distinct patterns or profiles for each of the
    75 medically relevant Mycobacterium species, including members of closely related Mycobacterium
    complex groups. This approach can quickly and reliably identify mycobacterial species, allowing for
    more timely treatment decisions and contributing to beneficial epidemiological investigations.
Research Authors
Mohmoud K Diab, Taysir Hassan A Soliman, Amr M Mohamed, Ibrahim E Elsemman
Research Date
Research Department
Research Journal
scientific reports-NATURE
Research Publisher
Scientific Reports
Research Year
2025
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