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bsj-3823
PDCNN: FRAMEWORK for Potato Diseases Classification Based on Feed Foreword Neural Network
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         The economy is exceptionally reliant on agricultural productivity. Therefore, in domain of agriculture, plant infection discovery is a vital job because it gives promising advance towards the development of agricultural production. In this work, a framework for potato diseases classification based on feed foreword neural network is proposed. The objective of this work  is presenting a system that can detect and classify four kinds of potato tubers diseases; black dot, common scab, potato virus Y and early blight based on their images. The presented PDCNN framework comprises three levels: the pre-processing is first level, which is based on K-means clustering algorithm to detect the infected area from potato image. The second level is features extraction which extracts features from the infected area based on hybrid features: grey level run length matrix and 1st order histogram based features. The attributes that extracted from second level are utilized in third level using FFNN to perform the classification process. The proposed framework is applied to database with different backgrounds, totally 120 color potato images, (80) samples used in training the network and the rest samples (40) used for testing. The proposed PDCNN framework is very effective in classifying four types of potato tubers diseases with 91.3% of efficiency.

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Publication Date
Sun Mar 30 2025
Journal Name
Studia Universitatis Babeș-bolyai Chemia
GREEN SPECTROPHOTOMETRIC METHOD FOR CONCURRENT ESTIMATION OF PIROXICAM AND MEFENAMIC ACID MIXTURE
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The purpose of this work is to concurrently estimate the UVvisible spectra of binary combinations of piroxicam and mefenamic acid using the chemometric approach. To create the model, spectral data from 73 samples (with wavelengths between 200 and 400 nm) were employed. A two-layer artificial neural network model was created, with two neurons in the output layer and fourteen neurons in the hidden layer. The model was trained to simulate the concentrations and spectra of piroxicam and mefenamic acid. For piroxicam and mefenamic acid, respectively, the Levenberg-Marquardt algorithm with feed-forward back-propagation learning produced root mean square errors of prediction of 0.1679 μg/mL and 0.1154 μg/mL, with coefficients of determination of

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Publication Date
Thu Aug 30 2018
Journal Name
Journal Of Engineering
Accuracy Assessment of Various Resolutions Digital Cameras For Close Range Photogrammetry Applications
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Due to the great evolution in digital commercial cameras, several studies have addressed the using of such cameras in different civil and close-range applications such as 3D models generation. However, previous studies have not discussed a precise relationship between a camera resolution and the accuracy of the models generated based on images of this camera. Therefore the current study aims to evaluate the accuracy of the derived 3D buildings models captured by different resolution cameras. The digital photogrammetric methods were devoted to derive 3D models using the data of various resolution cameras and analyze their accuracies. This investigation involves selecting three different resolution cameras (low, medium and

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Publication Date
Fri Jul 01 2016
Journal Name
Journal Of Engineering
Data Base for Dynamic Soil Properties of Seismic Active Zones in Iraq
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Iraq is located near the northern tip of the Arabian plate, which is advancing northwards relative to the Eurasian plate, and is predictably, a tectonically active country. Seismic activity in Iraq increased significantly during the last decade. So structural and geotechnical engineers have been giving increasing attention to the design of buildings for earthquake resistance. Dynamic properties play a vital role in the design of structures subjected to seismic load. The main objective of this study is to prepare a data base for the dynamic properties of different soils in seismic active zones in Iraq using the results of cross hole and down hole tests. From the data base collected it has been observed that the average ve

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Publication Date
Sat Apr 01 2023
Journal Name
Science Of The Total Environment
Recent advances and applicable flexibility potential of electrochemical processes for wastewater treatment
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This study examined >140 relevant publications from the last few years (2018–2021). In this study, classification was reviewed depending on the operation's progress. Electrocoagulation (EC), electrooxidation (EO), electroflotation (EF), electrodialysis (ED), and electro-Fenton (EFN) processes have received considerable attention. The type of action (individual or hybrid) for each electrochemical procedure was evaluated, and statistical analysis was performed to compare them as a new manner of reviewing cited papers providing a massive amount of information efficiently to the readers. Individual or hybrid operation progress of the electrochemical techniques is critical issues. Their design, operation, and maintenance costs vary depending o

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Publication Date
Sat Sep 01 2018
Journal Name
International Journal Of Applied Pharmaceutics
PREPARATION AND CHARACTERIZATION OF ECONAZOLE NITRATE INCLUSION COMPLEX FOR OCULAR DELIVERY SYSTEM
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Objective: Econazole nitrate (ECZ) is one of the triazole antifungal drugs with poor aqueous solubility and dissolution rate; there is a need for enhancement of solubility. Therefore; inclusion complexation with β cyclodextrin (βCD) was performed. Methods: In this study kneading method and co-evaporation method of preparation of inclusion complex between βCD and ECZ using two molar ratios of βCD. The solubility of these complexes in isotonic saline solution and distilled water was studied. Complexes prepared by kneading method were used for the preparation of different ophthalmic gel formulas using carbomer (CB) and sodium carboxymethylcellulose (sod CMC) as a gelling agent. The release profile and the rheological behaviour of the gel w

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Publication Date
Wed Oct 01 2025
Journal Name
Water Environment Research
Combining Electro Fenton With Adsorption Processes for Treatment of Petroleum Refinery Wastewater
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ABSTRACT<p> This study investigates the elimination of chemical oxygen demand (COD) from an Iraqi petroleum refinery effluent through a combined electro‐Fenton and adsorption process (EF+AC). Response surface methodology (RSM) with a Box–Behnken design (BBD) was employed to investigate the effects of FeSO <sub>4</sub> concentration, current density, and electrolysis time on the reduction of COD using the EF technique. According to the results of the analysis of variance (ANOVA) for the EF technique, FeSO <sub>4</sub> concentrations, with a contribution of 40.06%, and cur</p> ... Show More
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Publication Date
Thu Dec 01 2011
Journal Name
Swarm And Evolutionary Computation
Energy-aware evolutionary routing protocol for dynamic clustering of wireless sensor networks
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Publication Date
Mon Aug 01 2022
Journal Name
Water, Air And Soil Pollution
Cladophora Algae Modified with CuO Nanoparticles for Tetracycline Removal from Aqueous Solutions
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Modified algae with nano copper oxide (CuO) were used as adsorption media to remove tetracycline (TEC) from aqueous solutions. Functional groups, morphology, structure, and percentages of surfactants before and after adsorption were characterised through Fourier-transform infrared (FTIR), X-ray diffraction (XRD), scanning electron microscopy (SEM), and energy-dispersive spectroscopy (EDS). Several variables, including pH, connection time, dosage, initial concentrations, and temperature, were controlled to obtain the optimum condition. Thermodynamic studies, adsorption isotherm, and kinetics models were examined to describe and recognise the type of interactions involved. Resultantly, the best operation conditions were at pH 7, contact time

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Publication Date
Sun Jun 21 2020
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
Co-Amorphous System: A promising Strategy for Delivering Poorly Water - Soluble Drugs
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Amorphization of drug has been considered as an attractive approach in improving drug solubility and bioavailability. Unlike their crystalline counterparts, amorphous materials lack the long-range order of molecular packing and present the highest energy state of a solid material. Co-amorphous systems (CAM) are an innovative formulation technique by where the amorphous drugs are stabilized via powerful intermolecular interactions by means of a low molecular co-former.

This review highlights the different approaches in the preparation of co-amorphous drug delivery system, the proper selection of the co-formers. In addition, the recent advances in characterization, Industrial scale and formulation will be discussed.

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Publication Date
Thu Apr 20 2023
Journal Name
Fire
An Efficient Wildfire Detection System for AI-Embedded Applications Using Satellite Imagery
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Wildfire risk has globally increased during the past few years due to several factors. An efficient and fast response to wildfires is extremely important to reduce the damaging effect on humans and wildlife. This work introduces a methodology for designing an efficient machine learning system to detect wildfires using satellite imagery. A convolutional neural network (CNN) model is optimized to reduce the required computational resources. Due to the limitations of images containing fire and seasonal variations, an image augmentation process is used to develop adequate training samples for the change in the forest’s visual features and the seasonal wind direction at the study area during the fire season. The selected CNN model (Mob

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