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MODELS, DETECTION METHODS, AND CHALLENGES IN DC ARC FAULT: A REVIEW
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The power generation of solar photovoltaic (PV) technology is being implemented in every nation worldwide due to its environmentally clean characteristics. Therefore, PV technology is significantly growing in the present applications and usage of PV power systems. Despite the strength of the PV arrays in power systems, the arrays remain susceptible to certain faults. An effective supply requires economic returns, the security of the equipment and humans, precise fault identification, diagnosis, and interruption tools. Meanwhile, the faults in unidentified arc lead to serious fire hazards to commercial, residential, and utility-scale PV systems. To ensure secure and dependable distribution of electricity, the detection of such hazards is crucial in the early phases of the distribution. In this paper, a detailed review of modern approaches for the identification of DC arc faults in PV is presented. In addition, a thorough comparison is performed between various DC arc-fault models, characteristics, and approaches used for the identification of the faults.

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Publication Date
Fri Jan 01 2016
Journal Name
Statistics And Its Interface
Search for risk haplotype segments with GWAS data by use of finite mixture models
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The region-based association analysis has been proposed to capture the collective behavior of sets of variants by testing the association of each set instead of individual variants with the disease. Such an analysis typically involves a list of unphased multiple-locus genotypes with potentially sparse frequencies in cases and controls. To tackle the problem of the sparse distribution, a two-stage approach was proposed in literature: In the first stage, haplotypes are computationally inferred from genotypes, followed by a haplotype coclassification. In the second stage, the association analysis is performed on the inferred haplotype groups. If a haplotype is unevenly distributed between the case and control samples, this haplotype is labeled

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Publication Date
Fri Apr 22 2022
Journal Name
Periodicals Of Engineering And Natural Sciences (pen)
Developing models to predicting the effect of crises on construction projects using MLR technique
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Publication Date
Sun Dec 01 2019
Journal Name
Journal Of Economics And Administrative Sciences
Use Generalized Pareto Survival Models to Estimation Optimal Survival Time for Myocardial Infarction Patients
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The survival analysis is one of the modern methods of analysis that is based on the fact that the dependent variable represents time until the event concerned in the study. There are many survival models that deal with the impact of explanatory factors on the likelihood of survival, including the models proposed by the world, David Cox, one of the most important and common models of survival, where it consists of two functions, one of which is a parametric function that does not depend on the survival time and the other a nonparametric function that depends on times of survival, which the Cox model is defined as a semi parametric model, The set of parametric models that depend on the time-to-event distribution parameters such as

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Publication Date
Tue Dec 01 2020
Journal Name
Journal Of Engineering
Development of Regression Models for Predicting Pavement Condition Index from the International Roughness Index
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Flexible pavements are considered an essential element of transportation infrastructure. So, evaluations of flexible pavement performance are necessary for the proper management of transportation infrastructure. Pavement condition index (PCI) and international roughness index (IRI) are common indices applied to evaluate pavement surface conditions. However, the pavement condition surveys to calculate PCI are costly and time-consuming as compared to IRI. This article focuses on developing regression models that predict PCI from IRI. Eighty-three flexible pavement sections, with section length equal to 250 m, were selected in Al-Diwaniyah, Iraq, to develop PCI-IRI relationships. In terms of the quantity and severity of eac

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Publication Date
Sat Dec 31 2016
Journal Name
Al-kindy College Medical Journal
Comparison between Open Mini-incision Thyroidectomy and Conventional Thyroidectomy: Clinical Experience and Literatures Review
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Background: Thyroid surgery is most common endocrine surgery in general surgical practice. Objectives: the aim of this work is to evaluate the feasibility, benefits and outcomes of open mini-incision thyroidectomy and compared the results with that of conventional thyroidectomy. The comparison between the two groups was in term of incision length, amount of blood loss, time of operation, postoperative pain, hospital stay and the cosmetic outcomes.Type of the study: this is a single-blinded randomized controlled studyMethods: This study compared the advantages and outcomes of 22 patients subjected to mini-incision thyroidectomy (Group A) with the equal numbers of patients subjected to conventional thyroidectomy (Group B).Results: the oper

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Publication Date
Wed Oct 26 2022
Journal Name
Aims Geosciences
Calculation and determination of radioactivity in the old district of Najaf by using the track detector CR-39 and geographical information systems (GIS) methods
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This research aims to study the radiation concentration distribution of the old District of Najaf (Iraq), where 15 samples were taken from featured sites in the District, which represents archaeological, religious, and heritage sites. Track detector CR-39 was used to calculate the concentration of three different soil weights for each sample site after being exposed for a month. Geographical information systems (GIS) were used to distribute the radioactive concentration on the sites of the samples, where two interpolation methods, namely the inverse distance weight method (IDW) and the triangle irregular network method (NIT), to study the distribution of the radioactivity concentration. The study showed that the western part of the district

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Publication Date
Sat Jan 01 2022
Journal Name
Journal Of Al-farabi For Engineering Sciences Vol
Prototyping of Multi-Factors Based Vehicle Accident Detection and Reporting System Relying on GPS and GSM
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Publication Date
Sun Aug 01 2021
Journal Name
Journal Of Engineering
Practical comparation of the accuracy and speed of YOLO, SSD and Faster RCNN for drone detection
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Convolutional Neural Networks (CNN) have high performance in the fields of object recognition and classification. The strength of CNNs comes from the fact that they are able to extract information from raw-pixel content and learn features automatically. Feature extraction and classification algorithms can be either hand-crafted or Deep Learning (DL) based. DL detection approaches can be either two stages (region proposal approaches) detector or a single stage (non-region proposal approach) detector. Region proposal-based techniques include R-CNN, Fast RCNN, and Faster RCNN. Non-region proposal-based techniques include Single Shot Detector (SSD) and You Only Look Once (YOLO). We are going to compare the speed and accuracy of Faster RCNN,

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Publication Date
Tue Jan 01 2013
Journal Name
Innovative Systems Design And Engineering
Automated Surface Defect Detection using Area Scan Camera
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Publication Date
Mon May 15 2017
Journal Name
International Journal Of Image And Data Fusion
Image edge detection operators based on orthogonal polynomials
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