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bsj-6086
Perceptually Important Points-Based Data Aggregation Method for Wireless Sensor Networks
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The transmitting and receiving of data consume the most resources in Wireless Sensor Networks (WSNs). The energy supplied by the battery is the most important resource impacting WSN's lifespan in the sensor node. Therefore, because sensor nodes run from their limited battery, energy-saving is necessary. Data aggregation can be defined as a procedure applied for the elimination of redundant transmissions, and it provides fused information to the base stations, which in turn improves the energy effectiveness and increases the lifespan of energy-constrained WSNs. In this paper, a Perceptually Important Points Based Data Aggregation (PIP-DA) method for Wireless Sensor Networks is suggested to reduce redundant data before sending them to the sink. By utilizing Intel Berkeley Research Lab (IBRL) dataset, the efficiency of the proposed method was measured. The experimental findings illustrate the benefits of the proposed method as it reduces the overhead on the sensor node level up to 1.25% in remaining data and reduces the energy consumption up to 93% compared to prefix frequency filtering (PFF) and ATP protocols.

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Publication Date
Mon Jun 27 2022
Journal Name
Acs Omega
Development of Biodegradable/Biocompatible Nanoliposome-Encapsulated Antimicrobial Essential Oils for Topical Creams and Gels
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Publication Date
Fri Aug 01 2014
Journal Name
Journal Of Economics And Administrative Sciences
Preventive measures for banking supervision on money laundering (Search in the Gulf Commercial Bank)
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The research aims to study and assess the effectiveness of preventive measures banking for the reduction of money laundering based on the checklist (Check list), which have been prepared based on the paragraphs of some of the principles and recommendations of international and Money Laundering Act No. 93 of 2004 and the instructions thereto, to examine and assess the application of these measures by Gulf Commercial Bank, which was chosen to perform the search.

I've been a statement the concept of money laundering in terms of the definition and characteristics, stages and effects of political, economic and social as well as the nature of banking supervision in terms of the definition and the most important

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Publication Date
Thu Dec 04 2014
Journal Name
Engineering And Technology Journal
Optimization of the Time Required for Determination of the Total Dissolved Salts in Soil ‫
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Publication Date
Wed Jan 01 2020
Journal Name
Medico-legal Update
Flexible ureterorenoscopy versus extracorporeal shock wave lithotripsy for treatment of lower pole renal stones
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Publication Date
Sat Oct 31 2020
Journal Name
International Journal Of Psychosocial Rehabilitation
Attitudes of mothers towards over the counter antibiotics for their children in Baghdad city
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Publication Date
Mon Apr 17 2023
Journal Name
International Journal Of Veterinary Science And Medicine
Donor variability of ovine bone marrow derived mesenchymal stem cell - implications for cell therapy
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Publication Date
Wed Feb 22 2023
Journal Name
Iraqi Journal Of Science
Evaluation the Biosorption Capacity of Water Hyacinth (Eichhornia crassipes) Root for Some Heavy Metals
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Heavy metals especially lead (Pb), cadmium (Cd), chromium (Cr) and copper (Cu) are noxious pollutants with immense health hazards on living organisms, these pollutants enter aquatic environment in Iraq mainly Tigris and Euphrates rivers via waste water came from different anthropological activities, This study investigated capacity of dried and ground root of water hyacinth (Eichhornia crassipes) in removing the heavy metals from their aqueous solutions. Effects of initial concentrations of the heavy metals and pH of their aqueous solutions were studied. Results of this study revealed excellent biosorption capacity of water hyacinth root in general, removal of Pb was the highest and Cr was lowest. The results showed that the Pb, Cu and C

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Publication Date
Wed Jan 01 2014
Journal Name
International Journal Of Computer Applications
Enhancing the Delta Training Rule for a Single Layer Feedforward Heteroassociative Memory Neural Network
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In this paper, an algorithm is suggested to train a single layer feedforward neural network to function as a heteroassociative memory. This algorithm enhances the ability of the memory to recall the stored patterns when partially described noisy inputs patterns are presented. The algorithm relies on adapting the standard delta rule by introducing new terms, first order term and second order term to it. Results show that the heteroassociative neural network trained with this algorithm perfectly recalls the desired stored pattern when 1.6% and 3.2% special partially described noisy inputs patterns are presented.

Publication Date
Tue Jan 01 2019
Journal Name
International Journal Of Civil Engineering And Technology
Generalized tupled common fixed point theorems for weakly compatible mappings in fuzzy metric space
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Publication Date
Mon Aug 04 2014
Journal Name
Iraqi National Journal Of Chemistry
Comparative Study for Antibacterial Activity of Some Maleamic acid Derivatives with Some Commercial Antibiotic
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