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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 Apr 30 2023
Journal Name
Iraqi Journal Of Science
User Oriented Calibration Method for Stonex X300 Terrestrial Laser Scanner
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    Terrestrial laser scanners (TLSs) are 3D imaging systems that provide the most powerful 3D representation and practical solutions for various applications. Hence this is due to effective range measurements, 3D point cloud reliability, and rapid acquisition performance. Stonex X300 TOF scanner delivered better certainty in far-range than in close-range measurements due to the high noise level inherent within the data delivered from Time of Flight (TOF) scanning sensors. However, if these errors are manipulated properly using a valid calibration model, more accurate products can be obtained even from very close-range measurements. Therefore, to fill this gap, this research presents a user-oriented target-based calibration routi

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Publication Date
Fri Feb 18 2022
Journal Name
Coatings
Non-Polar Gallium Nitride for Photodetection Applications: A Systematic Review
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Ultraviolet photodetectors have been widely utilized in several applications, such as advanced communication, ozone sensing, air purification, flame detection, etc. Gallium nitride and its compound semiconductors have been promising candidates in photodetection applications. Unlike polar gallium nitride-based optoelectronics, non-polar gallium nitride-based optoelectronics have gained huge attention due to the piezoelectric and spontaneous polarization effect–induced quantum confined-stark effect being eliminated. In turn, non-polar gallium nitride-based photodetectors portray higher efficiency and faster response compared to the polar growth direction. To date, however, a systematic literature review of non-polar gallium nitride-

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Publication Date
Fri Oct 14 2022
Journal Name
Diagnostics
Determination of the Accuracy of Salivary Biomarkers for Periodontal Diagnosis
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Background: We aimed to investigate the accuracy of salivary matrix metalloproteinases (MMP)-8 and -9, and tissue inhibitor of metalloproteinase (TIMP)-1 in diagnosing periodontitis and in distinguishing periodontitis stages (S)1 to S3. Methods: This study was a case–control study that included patients with periodontitis S1 to S3 and subjects with healthy periodontia (controls). Saliva was collected, and then, clinical parameters were recorded, including plaque index, bleeding on probing, probing pocket depth, and clinical attachment level. Diagnosis was confirmed by assessing the alveolar bone level using radiography. Salivary biomarkers were assayed using an enzyme-linked immunosorbent assay. Results: A total of 45 patients (15

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Publication Date
Thu Mar 06 2025
Journal Name
Heat Transfer
Solar‐Powered Humidifiers for Humidification–Dehumidification Desalination Systems: A Review
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ABSTRACT<p>This work explores the advancement and potential of solar‐powered humidification–dehumidification (HDH) desalination systems, addressing the critical challenge of global water scarcity. Emphasizing solar‐powered humidifiers in HDH systems presents an innovative solution per the urgent demand for sustainable freshwater sources utilizing abundant energy resources. This work reviews various humidifier designs, pointing out their crucial role in the efficiency and yield of HDH desalination units and their operational, maintenance, and scaling issues. Key factors, such as design effectiveness, water‐vapor capacity, and material selection, are assessed to understand their impact on the system's ove</p> ... Show More
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Publication Date
Sun Jan 01 2023
Journal Name
Computers, Materials &amp; Continua
Hybrid Deep Learning Enabled Load Prediction for Energy Storage Systems
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Publication Date
Fri Jan 01 2021
Journal Name
Ieee Access
DNA Encoding and STR Extraction for Anomaly Intrusion Detection Systems
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Publication Date
Sun Mar 01 2026
Journal Name
Journal Of Engineering
A Dual-Stage Perceptual-Harmonic Hybrid Estimator for Speech Enhancement
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This paper proposes a hybrid speech enhancement estimator that integrates the Perceptually-motivated Karhunen–Loève Transform (PKLT) with the Dual-Masking Harmonic-based (DMH) algorithm in a unified framework termed PKDMH. The main novelty lies in combining perceptual subspace projection with harmonic-residual suppression, enabling the system to jointly remove noise while preserving speech-relevant spectral cues. PKLT first performs perceptual subspace projection and suppresses inaudible components, after which DMH eliminates remaining broadband and harmonic residuals. The proposed PKDMH system was evaluated using the TIMIT dataset contaminated with five noise types: White, Pink, F16, Airport, and Car noise—across five SNR leve

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Publication Date
Tue Jan 21 2025
Journal Name
Periodicals Of Engineering And Natural Sciences (pen)
A comparison between the hierarchical clustering methods for postgraduate students in Iraqi universities for the year 2019-2020 using the cophenetic and delta correlation coefficients
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The educational sector is one of the important sectors in the world, and it is considered one of the means of community development. In addition, it is one of the means of making the country’s renaissance and devel-opment because it represents the factory of thinking minds that make change. There is no doubt that this sector is the same as any other sector. The deficit in the studied scientific planning has been prolonged, which led to its deterioration, and the problems of education remain diverse and inherited from previous time periods, where the hierarchical cluster analysis was used on postgraduate students in universities in Iraq, except for Kurdistan region, and the number of universities that were included in the study was

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Publication Date
Mon May 18 2026
Journal Name
Al–bahith Al–a'alami
Evaluation of the Iraqi Community for Election Campaigns for Candidates of the House of Representatives and Media Coverage in March 2010: (Cairo as a Model)
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The elections of the Council of Representatives in Iraq are one of the manifestations of political participation, which makes it attracts the attention of researchers. Where Iraq witnessed in 2005 important political events in the Iraqi arena, a pluralist parliamentary elections or elections in Iraq by direct free election on January 30, the first almost half a century ago. On November 15 of the same year, Iraq adopted a permanent constitution for the country through a popular referendum.

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Publication Date
Fri Jul 01 2022
Journal Name
Sustainable Materials And Technologies
Green approach for fabrication of graphene from polyethylene terephthalate (PET) bottle waste as reactive material for dyes removal from aqueous solution: Batch and continuous study
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