جميل محمد علي محمد منى

Despite proposing a number of algorithms and protocols, especially those related to routing, for the purpose of reducing energy consumption in wireless sensor networks, which is one of the most important issues facing this type of network. In this research paper, energy consumption and cost are calculated taking into account energy consumption and the amount of data transferred to a thousand nodes through specific paths towards the mobile sink. The proposed model simulated by sending various amounts of data with specific path to know the energy consumption of each track and the network life time with 250, 500, and 1000 bits. Cost calculated using various weight for each track of these paths and the coefficient of movement time and path loss factor and others related to the transmission and receiving circuits. And finally, the results compared with a previous method it showed the efficiency of our method used and calculating 1000 nodes with various amount of bits to show the experimental results. Deep learning used to remember each and every path of each position or nearby to avoid calculation cost later.

Software engineering can be characterized as the definite examination of the engineering to the structure, the improvement and the support of the software. Software engineering models and methods are imposed on software architecture in order to make this movement efficient, repeatable and at last oriented towards success. Utilizing the models can be used in order to provide the way to deal with critical thinking, documentation, and strategies for the model development and the investigation. The Chronic Care Model (CCM) can be defined as the organizing framework which is used to improve the incessant ailment care and an astounding apparatus for improving consideration at both the individual and populace level. In this paper, one of the important CCM model parts, which is Self-management Support, will be improved in order to make the model more efficiency in the processing.

Ubiquitous technologies based heterogeneous networks has opened a new paradigm of technologies, which are enabled with various different objects called Internet of things (IoT). This field opens new door for innovative and advance patterns with considerable potential advantages in the shape of plethora of monitoring and infotainment applications around us. Data communication is one of the significant area of research in IoT due to its diverse network topologies, where diverse gadgets and devices have integrated and connected with each other. In order to communicate among devices and users, routing should be relible, secure and efficient. Due to diverse and hetrogenous netwok environment, the most of the existing routing solutions do not provide all quality of services requirement in the network. In this paper, we discuss the existing routing trend in IoT, vision and current challenges. This paper also elaborates the technologies and domains to drive this field for future perspectives. The paper concludes with discussion and main points for new researchers in terms of routing to understand about current situation in IoT.

Fingerprint is one of the broadly utilized biometric distinguishing proof to recognize the persons due steady and worthiness. The classification of fingerprints gives indexing to the dataset to decrease the seeking and matching manner. There researches have been developed numerous approaches for fingerprint classification model, for example, the Neural Network (NN) methods and support vector machine. Nevertheless, there are a lot of developments to develop the classification procedure. In this paper, a new classification model based on PSO-SVM technique is used to achieve fingerprint classification process. The proposed methodology comprises three phases: preprocessing phases, feature extraction phase and classification phase using the proposed PSO-SVM model. The CASIA V5 fingerprint dataset and a property dataset are adopted in this study to test the proposed model. The experimental results showed that the proposed PSO-SVM classification model was better than the standard SVM in terms of accuracy, sensitivity and specificity for both datasets

Abstract In this work, Nd:YAG laser with two wavelength (1064,532)nm was used in treating vascular (port wine stain, heamangioma ;and Telangiectase). Also Nd:YAG laser was used in tattoo treatment and the results achived is best than by using (KTP,PDL and Ar) laser. This process is occurs via absorption laser beam by skin layers, especially surface skin layer which is useful in the cosmetics surgical. There are different properties related with skin layer such as thermal diffusion and thermal relaxation time, the later is higher than the time of laser puls and this cause cooling to one –half without according thermal diffusion in normal (healthy) skin region. Nd:YAG laser can absorbed deeply and this observed when it used to remove the deep pigmentation, in compare with other laser types which absorbed only by the surface of skin layer because of low power , wavelength , frequencies and intensity in compare with Nd:YAG laser. Keyword: Nd:YAG laser, wavelength, treatment of superficial, superficial pigmentation, lasers.

التعرف على البرنامج التطبيقي مايكروسوفت وورد للمبتدئين والتعرف على معظم الرموز المستخدمة في البرنامج

ستقام ورشة عمل في نظام المواقع الالكترونية لتدريسيي جامعة الكوفة ولتدريسيي كلية الطب في مختبر الحاسبات التابع الى كلية الطب وذلك يوم الاربعاء المصادف 28/12/2016