Steganography is one of the most popular techniques for data hiding in the different media such as images, audio or video files. This paper introduced the improved technique to hide the secret message using the LSB algorithm inside the RGB true color image by encrypting it using the secret key transformation function. The key is selecting randomly in the GF (2n) with condition it has an inverse value to retrieve the encrypted message. Only two bits are used for the low byte in each pixel (the blue byte) to hide the secret message, since the blue color has a weak effect on human eyes. The message hidden by the suggested algorithm is less vulnerable to be stolen than other similar applications.

    The Fuzzy Logic method was implemented to detect and recognize English numbers in this paper. The extracted features within this method make the detection easy and accurate. These features depend on the crossing point of two vertical lines with one horizontal line to be used from the Fuzzy logic method, as shown by the Matlab code in this study. The font types are Times New Roman, Arial, Calabria, Arabic, and Andalus with different font sizes of 10, 16, 22, 28, 36, 42, 50 and 72. These numbers are isolated automatically with the designed algorithm, for which the code is also presented. The number’s image is tested with the Fuzzy algorithm depending on six-block properties only. Groups of regions (High, Medium, and Lo

<span>Dust is a common cause of health risks and also a cause of climate change, one of the most threatening problems to humans. In the recent decade, climate change in Iraq, typified by increased droughts and deserts, has generated numerous environmental issues. This study forecasts dust in five central Iraqi districts using machine learning and five regression algorithm supervised learning system framework. It was assessed using an Iraqi meteorological organization and seismology (IMOS) dataset. Simulation results show that the gradient boosting regressor (GBR) has a mean square error of 8.345 and a total accuracy ratio of 91.65%. Moreover, the results show that the decision tree (DT), where the mean square error is 8.965, c

     In this research, we propose to use two local search methods (LSM's); Particle Swarm Optimization (PSO) and the Bees Algorithm (BA) to solve Multi-Criteria Travelling Salesman Problem (MCTSP) to obtain the best efficient solutions. The generating process of the population of the proposed LSM's may be randomly obtained or by adding some initial solutions obtained from some efficient heuristic methods. The obtained solutions of the PSO and BA are compared with the solutions of the exact methods (complete enumeration and branch and bound methods) and some heuristic methods. The results proved the efficiency of PSO and BA methods for a large number of nodes ( ). The proposed LSM's give the best efficient solutions for the MCTSP for

 

    The combination of wavelet theory and neural networks has lead to the development of wavelet networks. Wavelet networks are feed-forward neural networks using wavelets as activation function. Wavelets networks have been used in classification and identification problems with some success.

  In this work we proposed a fuzzy wavenet network (FWN), which learns by common back-propagation algorithm to classify medical images. The library of medical image has been analyzed, first. Second, Two experimental tables’ rules provide an excellent opportunity to test the ability of fuzzy wavenet network due to the high level of information variability often experienced with this type of images.

&n

This paper presents a hybrid approach for solving null values problem; it hybridizes rough set theory with intelligent swarm algorithm. The proposed approach is a supervised learning model. A large set of complete data called learning data is used to find the decision rule sets that then have been used in solving the incomplete data problem. The intelligent swarm algorithm is used for feature selection which represents bees algorithm as heuristic search algorithm combined with rough set theory as evaluation function. Also another feature selection algorithm called ID3 is presented, it works as statistical algorithm instead of intelligent algorithm. A comparison between those two approaches is made in their performance for null values estima

Churning of employees from organizations is a serious problem. Turnover or churn of employees within an organization needs to be solved since it has negative impact on the organization. Manual detection of employee churn is quite difficult, so machine learning (ML) algorithms have been frequently used for employee churn detection as well as employee categorization according to turnover. Using Machine learning, only one study looks into the categorization of employees up to date.  A novel multi-criterion decision-making approach (MCDM) coupled with DE-PARETO principle has been proposed to categorize employees. This is referred to as SNEC scheme. An AHP-TOPSIS DE-PARETO PRINCIPLE model (AHPTOPDE) has been designed that uses 2-stage MCDM s

This paper presents a proposed neural network algorithm to solve the shortest path problem (SPP) for communication routing. The solution extends the traditional recurrent Hopfield architecture introducing the optimal routing for any request by choosing single and multi link path node-to-node traffic to minimize the loss. This suggested neural network algorithm implemented by using 20-nodes network example. The result shows that a clear convergence can be achieved by 95% valid convergence (about 361 optimal routes from 380-pairs). Additionally computation performance is also mentioned at the expense of slightly worse results.

The diplomatic bag is one of the important means of communication used by the diplomatic mission to communicate with the government of the sending country and its consulates, as well as the missions in other countries. The diplomatic bag was granted absolute immunity against opening, seizing and inspection in order to effectively perform the function entrusted to it. The practical reality revealed the exploitation of the diplomatic bag to smuggle drugs and shipments of weapons and explosives that harmed the national security of the receiving country. The International Law Committee avoided the matter and reconciled the interest of the immunity of the diplomatic bag with the interest of the state in preserving national security and sovere