Wireless sensor applications are susceptible to energy constraints. Most of the energy is consumed in communication between wireless nodes. Clustering and data aggregation are the two widely used strategies for reducing energy usage and increasing the lifetime of wireless sensor networks. In target tracking applications, large amount of redundant data is produced regularly. Hence, deployment of effective data aggregation schemes is vital to eliminate data redundancy. This work aims to conduct a comparative study of various research approaches that employ clustering techniques for efficiently aggregating data in target tracking applications as selection of an appropriate clustering algorithm may reflect positive results in the data aggregati

This research aims to removes dyes from waste water by adsorption using banana peels. The conduct experiment done by banana powder and banana gel to compare between them and find out which one is the most efficient in adsorption. Studying the effects different factors on adsorption material and calculate the best removal efficiency to get rid of the methylene blue dye (MB).

Background: Esthetic treatment is the options of patient seeking orthodontic treatment. Therefore this study was conducted to measure the concentration of Aluminum, Nickel, Chromium and Iron ions released from combination of monocrysralline brackets with different arch wires immersed in artificial saliva at different duration, to evaluate the corrosion point on different parts of the orthodontic appliances before and after immersion in artificial saliva, and to evaluate the corrosion potential of each group of the orthodontic appliances. Material and methods: Eighty orthodontic sets prepared. Each set represents half fixed orthodontic appliance, from the central incisor to the first molar, for the maxillary arch, each set consisted of molar

Feature selection (FS) constitutes a series of processes used to decide which relevant features/attributes to include and which irrelevant features to exclude for predictive modeling. It is a crucial task that aids machine learning classifiers in reducing error rates, computation time, overfitting, and improving classification accuracy. It has demonstrated its efficacy in myriads of domains, ranging from its use for text classification (TC), text mining, and image recognition. While there are many traditional FS methods, recent research efforts have been devoted to applying metaheuristic algorithms as FS techniques for the TC task. However, there are few literature reviews concerning TC. Therefore, a comprehensive overview was systematicall

ليس جديداً القول بان هناك حاجة مستمرة ومتزايدة لاستخدام البيانات الاقتصادية المتسقة عن القطاعات المختلفة في الاقتصاد القومي لدعم وإسناد عملية التحليل الاقتصادي وتطوير النماذج الاقتصادية الكلية.

وتعرض مصفوفة الحسابات القومية Social Accounting Matrix  (SAM) اطاراً شاملاً من المعلومات الأساسية لهذا النوع من النماذج والتحليل. فهي تتضمن كلا من المستخدم- المنتج
(

This paper discusses reliability R of the (2+1) Cascade model of inverse Weibull distribution. Reliability is to be found when strength-stress distributed is inverse Weibull random variables with unknown scale parameter and known shape parameter. Six estimation methods (Maximum likelihood, Moment, Least Square, Weighted Least Square, Regression and Percentile) are used to estimate reliability. There is a comparison between six different estimation methods by the simulation study by MATLAB 2016, using two statistical criteria Mean square error and Mean Absolute Percentage Error, where it is found that best estimator between the six estimators is Maximum likelihood estimation method.