In this paper we introduce and study special types of magic squares of order six. We list some enumerations of these squares. We present a parallelizable code. This code is based on the principles of genetic algorithms.

In this paper, a no reference blur image quality metric based on wavelet transform is presented. As blur affects specially edges and image fine details, most blur estimation algorithms, are based primarily on an adequate edge detection methods. Here we propose a new approach by analyzing edges through a multi-resolution decomposition. The ability of wavelets to extract the high frequency component of an image has made them useful for edge analysis through different resolutions. Moreover, the multi-resolution analysis is performed on reduced images size, and this could lead to an execution time improvement. In addition, the edges persistence through resolutions may be involved in accuracy blur quality measure estimation. To prove the validity of the proposed method, blurred images from LIVE data base have been considered. Results show that the proposed method provides an accurate quality measure.

Firstly it is needed to realize Wireless Sensors Networks (WSN); we can define it as the most important technologies in the new century. during the last decades there was many achievements especially in the field of micro sensor technology and the low power electronics have made WSNs and the reality of applications, WSNs enabled a great amount of the surveillance and supervision applications, especially for the hostile and the critical environments, such as the process of monitoring the sea. We are presented software and hardware platforms of the augmented sensor networks which should be connected in a temporal way to the back-end infrastructures to store the data storage and the interaction of the users, and it make a special use for the actuators or the devices which are considered a rich and special computing resource to manage a complex signal processing tasks. In our proposed solution, we attempt to deploy the sensors of the network which is used on the sea surface shall monitor the water characteristics such as temperature, PH, dissolved oxygen, etc., and provide various convenient services for end users who can manage the data via a website with spreadsheet from a long distance or applications in a console terminal. This project introduces the architecture of a WSN system, the hardware of the node, data acquisition, data processing with gateway, and data visualization. The schemes which are considered traditional one depend on the intensive work of the labor and the expensive hardware. We presented better solutions with special sensors to measure the characteristics of the water in Kuwait.

Finest Trail Setup Technique in Cloud Ambience[1] proposes a fuzzy logic based SVM approach to secure a collision free path avoiding multiple dynamic obstacles. The navigator consists of an FSVM -Based Collision Avoidance. The decisions are taken at each step for the providers & consumers to negotiate without collision. Fuzzy-SVM rule bases are built, which requires simple evaluation data based on the active participants in the Cloud at a given point of time. The effectiveness of the proposed method is verified by a series of simulations and implemented with a BOINC Manager. The time optimization algorithm that plans and responds a user request on auction-based resource allocation systems can be used for further improvement of Cloud broker services. Issues pertaining to scalability have to be addressed in this scenario. This dispute in the Cloud System can be addressed with Incremental FSVM with Kernel which will give better result in group nodes/clusters. Further to augment the technique, cloud service orchestration is applied. This enhances the approach by creating an application-aligned infrastructure that can be deployed by defining the policies. This paper displays a middleware Cloud Process Orchestration (CPO) for directing and observing computer-generated mechanisms into a Cloud computing environment.

The world is emerging in a comprehensive society and internet and other related technologies are becoming dominant and widespread, nations are inflowing to the digital phase. In the world of WWW, Moodle is used for instruction and learning in education. This study explored the effect of Moodle on students learning taking a course “Basic Computing Skills” offered for the foundation program at Sultan Qaboos University, Sultanate of Oman. Digital course material was used in the study. Students and instructors were continuously e- connected for exchanging their ideas, information, questions and answers. In response of their queries and discussions, required material and information were published on Moodle‟s course website. The results revealed that however students had little experience of Moodle at the beginning of the course but headed for the end they had valued the significance and use of Moodle as it is accessible from every internet enabled location at any time. They were comfortable using Moodle overall, and experienced its importance. Moodle also helped them in better understanding and learning the course material through the revision of their course web contents, and especially students preferred face to face approach, but supported with online Moodle activities as a favorite mode of learning.

Image recognition and understanding is one of the most interesting fields of researches. Its main idea is to bridge the gap between the high level human image understanding and the low level machine image representation. Quite a lot of applications have been suggested in different fields like medicine, industry, robotics, satellite imagery and other applications. This paper proposes a new approach of traffic signs image recognition and understanding using computational intelligent techniques and the application of this approach on intelligent cars which can recognize the traffic signs and take a decision according to the signs it reads. Supervised machine learning has been selected since the algorithm does not need to classify the images but to identify their precise meaning. Different neural networks have been trained and used in this paper. The best neural network has been selected, which uses genetic algorithms in its training, and is known as evolutionary training neural network. Different image features have also been investigated and discussed. the best of these features, which fit the requirement of the suggested algorithm, have been selected.

Motivated by the existence of two frequency bands and inspired from Lie algebra classification, we propose a new geometric cellular shape with double hexagonal structure. Based on a two dimensional root system of the exceptional Lie algebra G2, this cellular network model involves two hexagons of unequal side length at angle 30?. In this new hexagonal cellular networks, the principal hexagonal unit cell contains twelve coverage limits in contrast of the usual structure involving only six ones. Within the G2 hexagonal structure, two frequency bands can be now placed at the same sheet in contrast to the single hexagonal structure where it can appear only one frequency band. This double hexagonal structure can bring improvements for the operators and may allow them to enhance many new factors. In particular, it can be used to enhance security energy and spacial flexibility in cellular networks.