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Exact string matching is one of the critical issues in the field of computer science. This study proposed a hybrid string matching algorithm called E-AbdulRazzaq. This algorithm used the best properties of two original algorithms; AbdulRazzaq and Berry-Ravindran Algorithms. The proposed algorithm showed an efficient performance in the number of attempts and number of character comparison when compared the original and recent to the standard algorithms. The proposed algorithm was applied in several types of databases, which are DNA sequences, Protein sequences, XML structures, Pitch characters, English texts, and Source codes. The Pitch database was the best match for E-AbdulRazzaq with the number of attempts involving long and short patterns, while the DNA database was the worst match. No data is specified as the best or worst with the E-AbdulRazzaq algorithm in terms of the character comparisons. The E-AbdulRazzaq algorithms ranked first in most databases when using short and long patterns, in terms of number of attempts and character comparisons.

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String matching is considered as one of the center issues within the field of computer science, where there are numerous computer applications that supply the clients with string matching services. The increment within the number of databases which are created and protected in numerous computer gadgets had impacted researchers with the slant towards getting robust techniques in tending to this issue. In this study, the Maximum-Shift string matching algorithm is chosen to be executed with multi-core innovation through the utilization of OpenMP paradigm, in order to decrease the successive time, and increment the speedup and efficiency of the algorithm. The deoxyribonucleic acid (DNA), protein and the English text datasets are utilized to test the parallel execution that influences the Maximum-Shift algorithm execution when utilized with multi-core environment. The results demonstrated that the execution is affected by the performance between the parallel and consecutive execution of Maximum-Shift algorithm by data type. The English text appeared ideal comes about within the parallel execution time as compared to other datasets, whereas the DNA database set appeared the most elevated comes about when compared to other data types in terms of speedup and efficiency capabilities.

one of the popular things among succeeded companies is an automated system. The reasons behind using the automated system are to reduce human errors, work and to gain efficiency. The design focused on building an automated system for access control and attendance monitoring by the use of RFID technology. all the companies that still doing mural attendance will get a great help when it used the proposed system. this paper used RFID (tags, reader), microcontroller to collect data, ZigBee technology for transmitting and receiving data wirelessly, computer as a control station. the program at control station was written by using Visual C# and connect with database (DB) MSSQL server to store employees’ numbers (RFID tags) and used for attendance calculations. The initial results of the proposed system appear a high profit in time-saving and cost when compared with traditional systems. cost divided into two parts, firstly: a price of ZigBee device, secondly: security men

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Every day the networks are expanding in very large scale and running in very high speed. The Intrusion Detection System (IDS) becomes as an essential part in any new network structure. The IDS is relying on the string matching algorithm to detect any signature attack, but the high speed of the modern networks are preventing the IDS string matching algorithms to work properly. There is a need to develop a robust IDS string matching algorithms to overcome these weaknesses. In this paper, we continue to developing Boyer-Moore Horspool algorithm by adding a new multi-pattern hashing feature to its original structure, which is called MPH-BMH. The developed algorithm is able to reduce the matching time because it can compare a group of pattern at one time. The results show that MPH-BMH is around 50% faster than BMH and QS algorithms in which it can scan and match large number of network packets in the given time and consequently it can be very useful to work in high speed networks. 