Plagiarism is becoming more of a problem in academics. It’s made worse by the ease with which a wide range of resources can be found on the internet, as well as the ease with which they can be copied and pasted. It is academic theft since the perpetrator has ”taken” and presented the work of others as his or her own. Manual detection of plagiarism by a human being is difficult, imprecise, and time-consuming because it is difficult for anyone to compare their work to current data. Plagiarism is a big problem in higher education, and it can happen on any topic. Plagiarism detection has been studied in many scientific articles, and methods for recognition have been created utilizing the Plagiarism analysis, Authorship identification, and Near-duplicate detection (PAN) Dataset 2009- 2011. Verbatim plagiarism, according to the researchers, plagiarism is simply copying and pasting. They then moved on to smart plagiarism, which is more challenging to spot since it might include text change, taking ideas from other academics, and translation into a more difficult-to-manage language. Other studies have found that plagiarism can obscure the scientific content of publications by swapping words, removing or adding material, or reordering or changing the original articles. This article discusses the comparative study of plagiarism detection techniques.
Today’s modern medical imaging research faces the challenge of detecting brain tumor through Magnetic Resonance Images (MRI). Normally, to produce images of soft tissue of human body, MRI images are used by experts. It is used for analysis of human organs to replace surgery. For brain tumor detection, image segmentation is required. For this purpose, the brain is partitioned into two distinct regions. This is considered to be one of the most important but difficult part of the process of detecting brain tumor. Hence, it is highly necessary that segmentation of the MRI images must be done accurately before asking the computer to do the exact diagnosis. Earlier, a variety of algorithms were developed for segmentation of MRI images by usin
... Show MoreBackground: The study aimed to investigate the effect of different techniques of en masse retraction on the vertical and sagittal position, axial inclination, rate of space closure, and type of movement of maxillary central incisor. Materials and methods: A typodont simulation system was used (CL II division 2 malocclusion). Three groups were used group 1(N=10, T-loop), group 2(N=10, Time-Saving loop), and group 3(N=10, Microimplant). Photographs were taken before and after retraction and measurements were made using Autodesk AutoCAD© software 2010. Kruskal-Wallis one-way analyses of variance and Mann-Whitney U test (p?0.05) were used. Results: The rate of space closure showed no significant difference among the three groups (p?0.05), whi
... Show MoreBackground Solar irradiance is a nonlinear and intermittent function, which makes accurate forecasting of solar power generation a challenge. The high variability of meteorological conditions is not well represented by conventional atmospheric models, thus hampering forecasting skill and model robustness. In this work, an advanced hybridization of multi-population cuckoo search (HMPCS) algorithm with machine learning (ML) methods is developed to enhance the prediction performance of photovoltaic (PV) power forecasting with more reliability. Methods In this study, a hybrid modeling framework is proposed, called HMPCS–ML framework which captures the global search capacity of HMPCS and predictive power of sophisti
... Show MoreObjective: The descriptive study was used to evaluate nursing staff performance in cardiac care units at teaching
and non teaching hospitals in kirkuk city: A comparative study.
Methodology: A descriptive study was used to evaluate nursing staff performance in cardiac care units. The study
was conducted from December 29th
, 2013 up to the 27th of Apr. 2014. A non-probability (purposive) sample of
(44) nurses who work in cardiac care unit at Azady teaching Hospital and Kirkuk general Hospital was evaluated by
a questionnaire which consisted of two parts; the first part is concerned with the demographic characteristics of
the nurses and the second part concerned Observation check list for evaluation nursing staff Perfo
Abstract
Business organizations are using the technological innovations like cloud computing (CC) as a developmental platform in order to improve the performance of their information systems. In that context, our paper discusses know-how in employing the public and private CC to serve as platforms to develop the evaluation system of annual employees' performance (ESAEP) at Iraqi universities. Therefore, we ask the paper question which is “Is it possible to adopt the innovative solutions of ICTs (Like: public and private CC) for finding the developmental vision about management information systems at business organizations?”. In addition, the paper aim
... Show MoreObjectives: To compare early pregnancy outcomes, including miscarriage, ectopic pregnancy, multiple pregnancy, and congenital anomalies, among women who conceived following ovulation induction with letrozole or clomiphene citrate. Methods: A prospective comparative observational study was conducted at Al-Elwiya Maternity Teaching Hospital and a private clinic in Baghdad, Iraq, from March 2023 to December 2024. One hundred infertile women aged 21–35 years who conceived after ovulation induction with either letrozole (5 mg/day) or clomiphene citrate (100 mg/day) for five days (cycle days 3–7) were enrolled. Participants were followed through early pregnancy with serial sonography at 6, 8–11, and 18–20 weeks of gestation. Data
... Show MoreBackground: This study was conducted to assess the effect of sonic activation and bulk placement of resin composite in comparison to horizontal incremental placement on the fracture resistance of weakened premolar teeth. Materials and method: Sixty sound human single-rooted maxillary premolars extracted for orthodontic purposes were used in this study. Teeth were divided into six groups of ten teeth each: Group 1 (sound unprepared teeth as a control group), Group 2 (teeth prepared with MOD cavity and left unrestored), Group 3 (restored with SonicFill™ composite), Group 4 (restored with Quixfil™ composite), Group 5 (restored with Tertic EvoCeram® Bulk Fill composite) and Group 6 (restored with Universal Tetric EvoCeram® co
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