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Spiking Neural Network in Precision Agriculture
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In this paper, precision agriculture system is introduced based on Wireless Sensor Network (WSN). Soil moisture considered one of environment factors that effect on crop. The period of irrigation must be monitored. Neural network capable of learning the behavior of the agricultural soil in absence of mathematical model. This paper introduced modified type of neural network that is known as Spiking Neural Network (SNN). In this work, the precision agriculture system  is modeled, contains two SNNs which have been identified off-line based on logged data, one of these SNNs represents the monitor that located at sink where the period of irrigation is calculated and the other represents the soil. In addition, to reduce power consumption of sensor nodes Modified Chain-Cluster based Mixed (MCCM) routing algorithm is used. According to MCCM, the sensors will send their packets that are less than threshold moisture level to the sink. The SNN with Modified Spike-Prop (MSP) training algorithm is capable of identifying soil, irrigation periods and monitoring the soil moisture level, this means that SNN has the ability to be an identifier and monitor. By applying this system the particular agriculture area reaches to the desired moisture level.

 

 

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Publication Date
Sat Jun 01 2013
Journal Name
مجلة كلية بغداد للعلوم الاقتصادية الجامعة
Proposed family speech recognition
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Speech recognition is a very important field that can be used in many applications such as controlling to protect area, banking, transaction over telephone network database access service, voice email, investigations, House controlling and management ... etc. Speech recognition systems can be used in two modes: to identify a particular person or to verify a person’s claimed identity. The family speaker recognition is a modern field in the speaker recognition. Many family speakers have similarity in the characteristics and hard to identify between them. Today, the scope of speech recognition is limited to speech collected from cooperative users in real world office environments and without adverse microphone or channel impairments.

Publication Date
Tue Nov 24 2020
Journal Name
Experimental Heat Transfer
Thermal performance of a flat-plate solar collector using aqueous colloidal dispersions of multi-walled carbon nanotubes with different outside diameters
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The thermal performance of a flat-plate solar collector (FPSC) using novel heat transfer fluids of aqueous colloidal dispersions of covalently functionalized multi-walled carbon nanotubes with β-Alanine (Ala-MWCNTs) has been studied. Multi-walled carbon nanotubes (MWCNTs) with outside diameters of (< 8 nm) and (20–30 nm) having specific surface areas (SSAs) of (500 m2/g) and (110 m2/g), respectively, were utilized. For each Ala-MWCNTs, waterbased nanofluids were synthesized using weight concentrations of 0.025%, 0.05%, 0.075%, and 0.1%. A MATLAB code was built and a test rig was designed and developed. Heat flux intensities of 600, 800, and 1000 W/m2; mass flow rates of 0.6, 1.0, and 1.4 kg/min; and inlet fluid temperatures of 30, 40, an

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Publication Date
Thu Dec 01 2016
Journal Name
International Journal Of Vlsi Design & Communication Systems (vlsics)
SIMULTANEOUS OPTIMIZATION OF STANDBY AND ACTIVE ENERGY FOR SUB THRESHOLD CIRCUITS
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Increased downscaling of CMOS circuits with respect to feature size and threshold voltage has a result of dramatically increasing in leakage current. So, leakage power reduction is an important design issue for active and standby modes as long as the technology scaling increased. In this paper, a simultaneous active and standby energy optimization methodology is proposed for 22 nm sub-threshold CMOS circuits. In the first phase, we investigate the dual threshold voltage design for active energy per cycle minimization. A slack based genetic algorithm is proposed to find the optimal reverse body bias assignment to set of noncritical paths gates to ensure low active energy per cycle with the maximum allowable frequency at the optimal supply vo

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Publication Date
Sun Feb 25 2024
Journal Name
Baghdad Science Journal
An exploratory study of history-based test case prioritization techniques on different datasets
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In regression testing, Test case prioritization (TCP) is a technique to arrange all the available test cases. TCP techniques can improve fault detection performance which is measured by the average percentage of fault detection (APFD). History-based TCP is one of the TCP techniques that consider the history of past data to prioritize test cases. The issue of equal priority allocation to test cases is a common problem for most TCP techniques. However, this problem has not been explored in history-based TCP techniques. To solve this problem in regression testing, most of the researchers resort to random sorting of test cases. This study aims to investigate equal priority in history-based TCP techniques. The first objective is to implement

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Publication Date
Thu Feb 01 2024
Journal Name
Computers In Biology And Medicine
Model based smooth super-twisting control of cancer chemotherapy treatment
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Chemotherapy is one of the most efficient methods for treating cancer patients. Chemotherapy aims to eliminate cancer cells as thoroughly as possible. Delivering medications to patients’ bodies through various methods, either oral or intravenous is part of the chemotherapy process. Different cell-kill hypotheses take into account the interactions of the expansion of the tumor volume, external drugs, and the rate of their eradication. For the control of drug usage and tumor volume, a model based smooth super-twisting control (MBSSTC) is proposed in this paper. Firstly, three nonlinear cell-kill mathematical models are considered in this work, including the log-kill, Norton-Simon, and hypotheses subject to parametric uncertainties and exo

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Publication Date
Mon Apr 01 2024
Journal Name
Iop Conference Series: Earth And Environmental Science
Sustainable practices impact and planting date on yield of sorghum (Sorghum bicolor L. Moench)
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Environmental stress affects the yield of sorghum. This impact can be reduced by seed stimulation technique and determining the appropriate planting date. An experiment was conducted in the spring and fall seasons of 2022. Randomized complete block design with split-plot arrangement in four replications was used. Planting dates (spring season: February 15th, March 1st, 15th, April 1st, 15th; fall season: June 15th, July 1st, 15th, August 1st, 15th) were assigned to the main plots. Seed stimulation treatments (banana peel extract 35% + citric acid 100 mg L-1 and soaking in distilled water only) were applied to the subplots. The interaction treatment of soaking with banana peel extract + citric acid and the planting date of April 15th showed

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Publication Date
Tue Mar 31 2015
Journal Name
Al-khwarizmi Engineering Journal
Dual Measurements of Pressure and Temperature With Fiber Bragg Grating Sensor
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Abstract

The fiber Bragg grating (FBG) technology has been rapidly applied in the sensing technology field. In this work, uniform FBG was used as pressure sensor based on measuring related Bragg wavelength shift. The pressure was applied directly by air compressor to the sensor and the pressure was ranged from 1 to 6 bar.

      This sensor also was affected by the external temperature so as a result it could be used as a temperature sensor. This sensor could be used to monitor the pressure of dams. It has been shown from the result that the sensor is very sensitive to the pressure and the sensitivity was (67 pm\bar) and is very sensitive to temperature and the sensitivity was (10p

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Publication Date
Sat Apr 01 2017
Journal Name
Journal Of Economics And Administrative Sciences
Application the generalized estimating equation Method (GEE) to estimate of conditional logistic regression model for repeated measurements
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Conditional logistic regression is often used to study the relationship between event outcomes and specific prognostic factors in order to application of logistic regression and utilizing its predictive capabilities into environmental studies. This research seeks to demonstrate a novel approach of implementing conditional logistic regression in environmental research through inference methods predicated on longitudinal data. Thus, statistical analysis of longitudinal data requires methods that can properly take into account the interdependence within-subjects for the response measurements. If this correlation ignored then inferences such as statistical tests and confidence intervals can be invalid largely.

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Publication Date
Tue Dec 28 2021
Journal Name
Revue Des Recherches En Droit Et Sciences Politiques
The Concept of Contract Duration
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Time is an essential element of contracts، as there is an independent in many parts of each contract، but the time dimension has a significant impact on the provisions of all contracts and is not limited to a particular range of contracts، and French and Arab jurists alike have called for this dimension to be given special attention، and as a result the French legislator has introduced the term duration of the contract، to try to limit the temporal elements، to clarify their provisions and to distinguish between them in decree131/2 016، but for our Arab country it did not receive the appropriate answer. The problem of duration in contracts relates to the lack of clarity of the idea، and then to confuse the various time terms in the

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Publication Date
Thu Aug 07 2025
Journal Name
Journal Of Image And Graphics
Analysis Evolution of Image Caption Techniques: Combining Conventional and Modern Methods for Improvement
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This study explores the challenges in Artificial Intelligence (AI) systems in generating image captions, a task that requires effective integration of computer vision and natural language processing techniques. A comparative analysis between traditional approaches such as retrieval- based methods and linguistic templates) and modern approaches based on deep learning such as encoder-decoder models, attention mechanisms, and transformers). Theoretical results show that modern models perform better for the accuracy and the ability to generate more complex descriptions, while traditional methods outperform speed and simplicity. The paper proposes a hybrid framework that combines the advantages of both approaches, where conventional methods prod

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