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.

A total of 437 individuals of Turbellarin Platyhelminthes were sorted from benthic samples collected monthly for a period of seven months( April to November 2013 ) from AL-Dalmage lake, a part of middle section for main outfall drain south of Baghdad. They were identified as Gyratrix hermaphroditus, Stenostomum leucops ,Stenostomum unicolar and Stenostomum bryophilum ,The relative abundance of worms decreased during hot season which (May to September) ,where they start rising again. The species were studied alive , the identification criteria were illustrated by photos. G. hermaphroditus was the most abundant species among the four species.

The soil acari fauna of Citrus orchards of Baghdad in Jadiriya area was studied in a total
of forty-eight samples. Twenty-two species were recorded during the present study of which
eight species were first records to Iraq. The ordinal composition of the soil acari fauna was
predominantly Mesostigmata.
This fauna represents diverse trophic groups. The most abundant groups were the
predacious and the Microphytophagus, while the less abundant groups were the predacious/
Microphytophagus, Macrophytophagus, and Panaphytophagus. The most abundant and
frequent species were Rhizoglyphus sp. Tyrophagus putrescentiea (Scrank), Pachylaelaps
longisetis Halbt. and Stratiolaelaps miles Berl.

    In this study, the dung beetles Aphodius (Bodilus) ictericus (Laicharting, 1781) and Aphodius (Planolinellus) vittatus Say, 1825 which belongs to the family of Aphodiidae (Order: Coleoptera) are redscribed here as to being found for the first time in Iraq.

    The specimens were collected from different regions in the middle of Iraq; the main diagnostic characters and some morphological features of males were drawn and pictured.

planning is among the most significant in the field of robotics research.  As it is linked to finding a safe and efficient route in a cluttered environment for wheeled mobile robots and is considered a significant prerequisite for any such mobile robot project to be a success. This paper proposes the optimal path planning of the wheeled mobile robot with collision avoidance by using an algorithm called grey wolf optimization (GWO) as a method for finding the shortest and safe. The research goals in this study for identify the best path while taking into account the effect of the number of obstacles and design parameters on performance for the algorithm to find the best path. The simulations are run in the MATLAB environment to test the

A new modified differential evolution algorithm DE-BEA, is proposed to improve the reliability of the standard DE/current-to-rand/1/bin by implementing a new mutation scheme inspired by the bacterial evolutionary algorithm (BEA). The crossover and the selection schemes of the DE method are also modified to fit the new DE-BEA mechanism. The new scheme diversifies the population by applying to all the individuals a segment based scheme that generates multiple copies (clones) from each individual one-by-one and applies the BEA segment-wise mechanism. These new steps are embedded in the DE/current-to-rand/bin scheme. The performance of the new algorithm has been compared with several DE variants over eighteen benchmark functions including sever

This paper presents an improved technique on Ant Colony Optimization (ACO) algorithm. The procedure is applied on Single Machine with Infinite Bus (SMIB) system with power system stabilizer (PSS) at three different loading regimes. The simulations are made by using MATLAB software. The results show that by using Improved Ant Colony Optimization (IACO) the system will give better performance with less number of iterations as it compared with a previous modification on ACO. In addition, the probability of selecting the arc depends on the best ant performance and the evaporation rate.

A Strength Pareto Evolutionary Algorithm 2 (SPEA 2) approach for solving the multi-objective Environmental / Economic Power Dispatch (EEPD) problem is presented in this paper. In the past fuel cost consumption minimization was the aim (a single objective function) of economic power dispatch problem. Since the clean air act amendments have been applied to reduce SO2 and NOX emissions from power plants, the utilities change their strategies in order to reduce pollution and atmospheric emission as well, adding emission minimization as other objective function made economic power dispatch (EPD) a multi-objective problem having conflicting objectives. SPEA2 is the improved version of SPEA with better fitness assignment, density estimation, an

This work presents a symmetric cryptography coupled with Chaotic NN , the encryption algorithm process the data as a blocks and it consists of multilevel( coding of character, generates array of keys (weights),coding of text and chaotic NN ) , also the decryption process consists of multilevel (generates array of keys (weights),chaotic NN, decoding of text and decoding of character).Chaotic neural network is used as a part of the proposed system with modifying on it ,the keys that are used in chaotic sequence are formed by proposed key generation algorithm .The proposed algorithm appears efficiency during the execution time where it can encryption and decryption long messages by short time and small memory (chaotic NN offer capacity of m