Metaheuristics under the swarm intelligence (SI) class have proven to be efficient and have become popular methods for solving different optimization problems. Based on the usage of memory, metaheuristics can be classified into algorithms with memory and without memory (memory-less). The absence of memory in some metaheuristics will lead to the loss of the information gained in previous iterations. The metaheuristics tend to divert from promising areas of solutions search spaces which will lead to non-optimal solutions. This paper aims to review memory usage and its effect on the performance of the main SI-based metaheuristics. Investigation has been performed on SI metaheuristics, memory usage and memory-less metaheuristics, memory char

In this paper, the using of Non-Homogenous Poisson Processes, with one of the scientific and practical means in the Operations Research had been carried out, which is the Queuing Theory, as those operations are affected by time in their conduct by one function which has a cyclic behavior, called the (Sinusoidal Function). (M_t / M / S) The model was chosen, and it is Single Queue Length with multiple service Channels, and using the estimating scales (QL_s, HOL, HOL_r) was carried out in considering the delay occurring to the customer before his entrance to the service, with the comparison of the best of them in the cases of the overload.

Through the experiments

Because of vulnerable threats and attacks against database during transmission from sender to receiver, which is one of the most global security concerns of network users, a lightweight cryptosystem using Rivest Cipher 4 (RC4) algorithm is proposed. This cryptosystem maintains data privacy by performing encryption of data in cipher form and transfers it over the network and again performing decryption to original data. Hens, ciphers represent encapsulating system for database tables

The power of advertising is immense. Producers of commercial goods and services routinely pour vast sums into promoting their wares through the advertising media, knowing  that a successful campaign can win them vital market share , and that failure to advertise effectively can have devastating results . The function of advertising is promotional ; to draw our  attention. In order  to achieve this function it must reach its target  audience , then capture that audience with a message that is both attractive and memorable.

         From a linguistic point of view, the language of advertising must be informative, instructive , distinctive and persuasive . It must employ&nb

Bacterial contamination of AL-Habania and AL-Tharthar reservoirs were studied during the period from February 2001 to January 2002, samples were collected from four stations in AL-Habania reservoir (AL-Warrar, AL-Theban regulator, middle of the reservoir and the fourth was towards AL-Razzaza reservoir) and from two stations at AL-Tharthar reservoir (Ein AL-Hilwa and the middle of the reservoir). Coliform bacteria, faecal Coliforms, Streptococci, faecal Streptococci and total count of bacteria were used as parameters of bacterial contamination in waters of both reservoirs through calculating the most probable number. Highest count of Coliform bacteria (15000 cell/100ml) was recorded at Ein AL-Hilwa and lowest count at AL-Theban regulator

Abstract  

  In this work, two algorithms of Metaheuristic algorithms were hybridized. The first is Invasive Weed Optimization algorithm (IWO) it is a numerical stochastic optimization algorithm and the second is Whale Optimization Algorithm (WOA) it is an algorithm based on the intelligence of swarms and community intelligence. Invasive Weed Optimization Algorithm (IWO) is an algorithm inspired by nature and specifically from the colonizing weeds behavior of weeds, first proposed in 2006 by Mehrabian and Lucas. Due to their strength and adaptability, weeds pose a serious threat to cultivated plants, making them a threat to the cultivation process. The behavior of these weeds has been simulated and used in Invas

Abstract: Data mining is become very important at the present time, especially with the increase in the area of information it's became huge, so it was necessary to use data mining to contain them and using them, one of the data mining techniques are association rules here using the Pattern Growth method kind enhancer for the apriori. The pattern growth method depends on fp-tree structure, this paper presents modify of fp-tree algorithm called HFMFFP-Growth by divided dataset and for each part take most frequent item in fp-tree so final nodes for conditional tree less than the original fp-tree. And less memory space and time.