Realizing the full potential of wireless sensor networks (WSNs) highlights many design issues, particularly the trade-offs concerning multiple conflicting improvements such as maximizing the route overlapping for efficient data aggregation and minimizing the total link cost. While the issues of data aggregation routing protocols and link cost function in a WSNs have been comprehensively considered in the literature, a trade-off improvement between these two has not yet been addressed. In this paper, a comprehensive weight for trade-off between different objectives has been employed, the so-called weighted data aggregation routing strategy (WDARS) which aims to maximize the overlap routes for efficient data aggregation and link cost issues in cluster-based WSNs simultaneously. The proposed methodology is evaluated for energy consumption, network lifetime, throughput, and packet delivery ratio and compared with the InFRA and DRINA. These protocols are cluster-based routing protocols which only aim to maximize the overlap routes for efficient data aggregation. Analysis and simulation results revealed that the WDARS delivered a longer network lifetime with more proficient and reliable performance over other methods.
Social responsibility has achieved tremendous attention by academicians and practitioners to focus on social responsibility accounting. However, many studies around the globe have been conduct to measure the outcomes of social responsibility accounting. This paper presents the impact of applying the supply chain strategy (SCS) on the agribusiness field to optimize productivity and decreasing cost which will have a direct impact on the net income of the organization. The inconclusive results of earlier studies stimulated this research to social responsibility accounting-financial performance. The equivocal results of this phenomenon urge this study to investigate the role of other factors in the relationship of social responsibility accounti
... Show MoreABSTRACT
Threw this research to the following:
1 - Know the impact of strategy Puglia in the collection of the rules of the Arabic language
students at the Institute of preparation parameters .
2 - Know the impact of the retention strategy in Puglia collection rules Arabic language
students at the Institute of preparation parameters .
To verify the status Mmermaa Find researcher Elsafreeten following two hypotheses :
1 - There is no statistically significant difference between the average score for the collection
of the fourth grade students at the Institute for the preparation of material parameters who
were studying grammar strategy Puglia and average grades collectible fourth grade
students at the Institu
The research aims to identify the impact of the visual teaching strategy by using infographics mathematics achievement for intermediate grade students. The experimental research method was adopted, as the experimental design of two independent and equal groups with a post test was used, whereas the experiment was applied on a sample consisting of (52) male students from first- intermediate grade students in (Al-Haq Al-Mubin intermediate school for Boys) of the General Directorate in Anbar Governorate - Department Education in Fallujah for the academic year (2021-2022), and the research sample was distributed equally on the two research groups, and Division (B) was chosen randomly to be the experimental group, while Division (A) was the cont
... Show MoreThis study dealt with the management strategy as an independent variable and the integrated industrial distribution as a variable. The study aimed at finding the integrated industrial distribution that fits with the management strategy in providing the needs of the firm on the one hand and reducing the cost of management that is reflected in increasing its profits.
The researcher selected the data from (130) decision makers in the corporation and used the questionnaire as a tool for collecting data and used a set of statistical tools and tools suitable for the nature of information and were processed using the data analysis system (SPSS version 24) Based on the analysis of the responses of the sample and the test of correlation and
The present study dealt with the removal of methylene blue from wastewater by using peanut hulls (PNH) as adsorbent. Two modes of operation were used in the present work, batch mode and inverse fluidized bed mode. In batch experiment, the effect of peanut hulls doses 2, 4, 8, 12 and 16 g, with constant initial pH =5.6, concentration 20 mg/L and particle size 2-3.35 mm were studied. The results showed that the percent removal of methylene blue increased with the increase of peanut hulls dose. Batch kinetics experiments showed that equilibrium time was about 3 hours, isotherm models (Langmuir and Freundlich) were used to correlate these results. The results showed that the (Freundlich) model gave the best fitting for adsorption capacity. D
... Show MoreThis research highlights the light on the general framework of accounting discloser in the Islamic banks, and show the types and the concepts of Cost Efficiency, In this present study, the sample included Fourteen Islamic banks, where the data was collected from the annual financial reports. Accordingly, the study in order to achieve the aims and access to the results based on the analytical method and the descriptive analysis, and conducted a Simple & Multiple Linear Regression analysis, in order to test hypotheses of the research by using of statistical analysis software (SPSS). The research has arrived to many results such as: the commitment of Islamic banks working in the Kingdome of Bahrain (Wholesale) to the requirements of the
... Show More. In recent years, Bitcoin has become the most widely used blockchain platform in business and finance. The goal of this work is to find a viable prediction model that incorporates and perhaps improves on a combination of available models. Among the techniques utilized in this paper are exponential smoothing, ARIMA, artificial neural networks (ANNs) models, and prediction combination models. The study's most obvious discovery is that artificial intelligence models improve the results of compound prediction models. The second key discovery was that a strong combination forecasting model that responds to the multiple fluctuations that occur in the bitcoin time series and Error improvement should be used. Based on the results, the prediction a
... Show MoreIn recent years, Bitcoin has become the most widely used blockchain platform in business and finance. The goal of this work is to find a viable prediction model that incorporates and perhaps improves on a combination of available models. Among the techniques utilized in this paper are exponential smoothing, ARIMA, artificial neural networks (ANNs) models, and prediction combination models. The study's most obvious discovery is that artificial intelligence models improve the results of compound prediction models. The second key discovery was that a strong combination forecasting model that responds to the multiple fluctuations that occur in the bitcoin time series and Error improvement should be used. Based on the results, the prediction acc
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