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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
Sun Nov 27 2022
Journal Name
مجلة البحوث الجغرافية
مجلة البحوث الجغرافية
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عتبر البصمة الكربونية ذات تأثير كبير في تحسين بيئة المدينة والمحافظة عمى استدامتيا ، فزيادتيا تعتبر مؤشر عمى التدىور البيئي بسبب زيادة انبعاثات غازات االحتباس الحراري ، وأىميا غاز COالذي ينتج من احتراق مئات بل باليين األطنان من الوقود األحفوري بإستخدام المنشآت الصناعية ومحطات الطاقة ووسائل النقل المختمفة، حيث ان في كل عام يتم انبعاث ما يقارب من 02 مميار طن من غاز CO ،وكذلك غاز CH الذي ينتج بسبب العديد من النشاطا

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Publication Date
Sun Nov 01 2015
Journal Name
Journal Of Engineering
Greening Existing Buildings in Contemporary Iraqi Urban Reality/ Virtual Model
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The approach of greening existing buildings, is an urgent necessity, because the greening operation provides the speed and optimal efficiency in the environmental performance, as well as keeping up with the global green architecture revolution. Therefore, greening existing buildings in Iraq is important for trends towards renewable energies, because of what the country went through economic conditions and crises and wars which kept the country away from what took place globally in this issue. The research problem is: insufficient knowledge about the importance and the mechanism of the greening of existing buildings, including its environmental and economic dimensions, by rationalization of energy consumption and preservi

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Publication Date
Fri Nov 20 2020
Journal Name
Agriculture
Predicting Phosphorus and Potato Yield Using Active and Passive Sensors
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Applications of remote sensing are important in improving potato production through the broader adoption of precision agriculture. This technology could be useful in decreasing the potential contamination of soil and water due to the over-fertilization of agriculture crops. The objective of this study was to assess the utility of active sensors (Crop Circle™, Holland Scientific, Inc., Lincoln, NE, USA and GreenSeeker™, Trimble Navigation Limited, Sunnyvale, CA, USA) and passive sensors (multispectral imaging with Unmanned Arial Vehicles (UAVs)) to predict total potato yield and phosphorus (P) uptake. The experimental design was a randomized complete block with four replications and six P treatments, ranging from 0 to 280 kg P ha−1, as

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Publication Date
Sun Jan 10 2016
Journal Name
British Journal Of Applied Science & Technology
The Effect of Classification Methods on Facial Emotion Recognition ‎Accuracy
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The interests toward developing accurate automatic face emotion recognition methodologies are growing vastly, and it is still one of an ever growing research field in the region of computer vision, artificial intelligent and automation. However, there is a challenge to build an automated system which equals human ability to recognize facial emotion because of the lack of an effective facial feature descriptor and the difficulty of choosing proper classification method. In this paper, a geometric based feature vector has been proposed. For the classification purpose, three different types of classification methods are tested: statistical, artificial neural network (NN) and Support Vector Machine (SVM). A modified K-Means clustering algorithm

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Publication Date
Sun Feb 25 2024
Journal Name
Baghdad Science Journal
Human Pose Estimation Algorithm Using Optimized Symmetric Spatial Transformation Network
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Human posture estimation is a crucial topic in the computer vision field and has become a hotspot for research in many human behaviors related work. Human pose estimation can be understood as the human key point recognition and connection problem. The paper presents an optimized symmetric spatial transformation network designed to connect with single-person pose estimation network to propose high-quality human target frames from inaccurate human bounding boxes, and introduces parametric pose non-maximal suppression to eliminate redundant pose estimation, and applies an elimination rule to eliminate similar pose to obtain unique human pose estimation results. The exploratory outcomes demonstrate the way that the proposed technique can pre

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Publication Date
Sat Jul 18 2026
Journal Name
Al–bahith Al–a'alami
EMPLOYING TWITTER IN THE U.S. PRESIDENTIAL ELECTION CAMPAIGN IN 2016: U.S. PRESIDENTIAL CANDIDATE DONALD TRUMP’S TWEETS AS A “MODEL”: (A Research Drawn from a Master’s Thesis) (An Analytical Study)
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This study aimed to identify the employment of the social networking platform «Twitter» in the 2016 presidential campaign led by the Republican candidate, Donald Trump; and analyse his tweets through his personal account on «Twitter»  for the period from: 10/ 8/2016 to: 11/ 8/2016 which represents the last month of the election campaign.

The study belongs to the type of descriptive studies using the analytical method through an analysis index that includes sub-categories and other secondary categories. The research has adopted the ordinary unit of information material (tweet) as an analysis unit for this purpose.

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Publication Date
Sun Jun 06 2010
Journal Name
Baghdad Science Journal
Using Neural Network with Speaker Applications
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In Automatic Speech Recognition (ASR) the non-linear data projection provided by a one hidden layer Multilayer Perceptron (MLP), trained to recognize phonemes, and has previous experiments to provide feature enhancement substantially increased ASR performance, especially in noise. Previous attempts to apply an analogous approach to speaker identification have not succeeded in improving performance, except by combining MLP processed features with other features. We present test results for the TIMIT database which show that the advantage of MLP preprocessing for open set speaker identification increases with the number of speakers used to train the MLP and that improved identification is obtained as this number increases beyond sixty.

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Publication Date
Tue Dec 05 2023
Journal Name
Engineering, Technology & Applied Science Research
Theoretical Analysis of Composite RC Beams with Pultruded GFRP Beams subjected to Impact Loading
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Glass Fiber Reinforced Polymer (GFRP) beams have gained attention due to their promising mechanical properties and potential for structural applications. Combining GFRP core and encasing materials creates a composite beam with superior mechanical properties. This paper describes the testing encased GFRP beams as composite Reinforced Concrete (RC) beams under low-velocity impact load. Theoretical analysis was used with practical results to simulate the tested beams' behavior and predict the generated energies during the impact loading. The impact response was investigated using repeated drops of 42.5 kg falling mass from various heights. An analysis was performed using accelerometer readings to calculate the generalized inertial load. The in

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Publication Date
Fri Jul 01 2016
Journal Name
International Journal Of Advanced Research
Attenuation Coefficient of Reactive Powder Concrete Using Different Energies.
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Linear and mass attenuation coefficient of reactive powder concrete (RPC) sample ( of compressive strength equal to 70 Mpa) using beta particles and gamma ray with different energies have been calculated as a function of the absorber thickness and energy. The attenuation coefficient were obtained using NaI(Tl) energy selective scintillation counter with 90Sr/90Y beta source having an energy rang from (0.546-2.274) MeV and gamma ray energies (0.569, 0.662, 1.063, 1.17 and 1.33) MeV . The attenuation coefficient usually depends upon the energy of radiations and nature of the material. The result represented in graphical forms. Exponential decay was observed. It is found that the capability of reactive powder concrete to absorber beta particle

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Publication Date
Fri Nov 29 2019
Journal Name
Iraqi Journal Of Physics
Gas Sensing of (SnO2)1-x(ZnO)x Composite Associating with Electrical Properties
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Abstract

Semiconductor-based gas sensors were prepared, that use n-type tin oxide (SnO2) and  tin oxide: zinc oxide composite (SnO2)1-x(ZnO)x at different x ratios using pulse laser deposition at room temperature. The prepared thin films were examined to reach the optimum conditions for gas sensing applications, namely X-ray diffraction, Hall effect measurements, and direct current conductivity. It was found that the optimum crystallinity and maximum electron density, corresponding to the minimum charge carrier mobility, appeared at 10% ZnO ratio. This ratio appeared has the optimum NO2 gas sensitivity for 5% gas concentration at 300 °C working temperat

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