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Combinatorial Testing Approaches: A Systematic Review
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Testing is a vital phase in software development, and having the right amount of test data is an important aspect in speeding up the process. As a result of the integrationist optimization challenge, extensive testing may not always be practicable. There is also a shortage of resources, expenses, and schedules that impede the testing process. One way to explain combinational testing (CT) is as a basic strategy for creating new test cases. CT has been discussed by several scholars while establishing alternative tactics depending on the interactions between parameters. Thus, an investigation into current CT methods was started in order to better understand their capabilities and limitations. In this study, 97 publications were evaluated based on a variety of criteria, including the generation technology, test strategy method, supported interactions, mixed coverage ,and support constraints between parameters. CT analysis had a wide range of interaction assistance options available to researchers. Since 2010, a unified interaction has been the most common style of interaction between the two parties. The year 2018 was hailed as the most successful in terms of CT by researchers. Researchers should focus on one test at a time and metaheuristic search strategies for t-way CT. There has also been a significant increase in the popularity of other trends, such as deep learning (DL). CT appears to be a useful testing technique for balancing and fault detection capabilities for a variety of systems and applications, according to our research. Future research and software development may benefit from this information. Index Terms— Combinatorial Testing, Test Case Generation, Optimization Algorithms, Software Testing, Artificial Intelligent.

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Publication Date
Sun Jul 24 2022
Journal Name
Healthcare
Incidence of Gingival Black Triangles following Treatment with Fixed Orthodontic Appliance: A Systematic Review
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This systematic review aimed to investigate the relation between orthodontic treatment (OT) and the incidence of the gingival black triangle (GBT) after completing treatment with a fixed orthodontic appliance, as well as the associated risk factors and the level of alveolar bone. Electronic and hand searches were conducted in three electronic databases for relevant articles published up to March 2022. Retrieved articles went through a two-step screening procedure, and the risk of bias (RoB) was assessed by the Joanna Briggs Institute checklists. The incidence of GBT after OT was set as the primary outcome, while the secondary outcomes were the risk factors associated with GBT and alveolar bone loss following OT. Out of 421 papers, 5

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Publication Date
Wed Mar 30 2022
Journal Name
Iraqi Journal Of Science
Modeling Social Networks using Data Mining Approaches-Review
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     Getting knowledge from raw data has delivered beneficial information in several domains. The prevalent utilizing of social media produced extraordinary quantities of social information. Simply, social media delivers an available podium for employers for sharing information. Data Mining has ability to present applicable designs that can be useful for employers, commercial, and customers. Data of social media are strident, massive, formless, and dynamic in the natural case, so modern encounters grow. Investigation methods of data mining utilized via social networks is the purpose of the study, accepting investigation plans on the basis of criteria, and by selecting a number of papers to serve as the foundation for this arti

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Publication Date
Wed Mar 08 2023
Journal Name
Sensors
A Critical Review of Remote Sensing Approaches and Deep Learning Techniques in Archaeology
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To date, comprehensive reviews and discussions of the strengths and limitations of Remote Sensing (RS) standalone and combination approaches, and Deep Learning (DL)-based RS datasets in archaeology have been limited. The objective of this paper is, therefore, to review and critically discuss existing studies that have applied these advanced approaches in archaeology, with a specific focus on digital preservation and object detection. RS standalone approaches including range-based and image-based modelling (e.g., laser scanning and SfM photogrammetry) have several disadvantages in terms of spatial resolution, penetrations, textures, colours, and accuracy. These limitations have led some archaeological studies to fuse/integrate multip

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Publication Date
Fri Sep 24 2021
Journal Name
Applied Sciences
The Impact of Calcitriol on Orthodontic Tooth Movement: A Cumulative Systematic Review and Meta-Analysis
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A cumulative review with a systematic approach aimed to provide a comparison of studies’ investigating the possible impact of the active form of vitamin D3, calcitriol (CTL), on the tooth movement caused by orthodontic forces (OTM) by evaluating the quality of evidence, based on collating current data from animal model studies, in vivo cell culture studies, and human clinical trials. Methods: A strict systematic review protocol was applied following the application of the International Prospective Register of Systematic Reviews (PROSPERO). A structured search strategy, including main keywords, was defined during detailed search with the application of electronic database systems: Medline/Pubmed, EMBASE, Scopus, Web of Science, and

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Publication Date
Fri Jun 30 2023
Journal Name
Iraqi Journal Of Science
Review on Vision Based Real Time Fingertip Detection Approaches
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    Computer vision is an emerging area with a huge number of applications. Identification of the fingertip is one of the major parts of those areas. Augmented reality and virtual reality are the most recent technological advancements that use fingertip identification. The interaction between computers and humans can be performed easily by this technique. Virtual reality, robotics, smart gaming are the main application domains of these fingertip detection techniques. Gesture recognition is one of the most fascinating fields of fingertip detection. Gestures are the easiest and productive methods of communication with regard to collaboration with the computer. This analysis examines the different studies done in the field of

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Publication Date
Sat Jan 01 2022
Journal Name
Ieee Access
Wrapper and Hybrid Feature Selection Methods Using Metaheuristic Algorithms for English Text Classification: A Systematic Review
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Feature selection (FS) constitutes a series of processes used to decide which relevant features/attributes to include and which irrelevant features to exclude for predictive modeling. It is a crucial task that aids machine learning classifiers in reducing error rates, computation time, overfitting, and improving classification accuracy. It has demonstrated its efficacy in myriads of domains, ranging from its use for text classification (TC), text mining, and image recognition. While there are many traditional FS methods, recent research efforts have been devoted to applying metaheuristic algorithms as FS techniques for the TC task. However, there are few literature reviews concerning TC. Therefore, a comprehensive overview was systematicall

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Publication Date
Sun Dec 01 2019
Journal Name
Journal Of Coloproctology
Rectal cancer and chemoradiation in Iraq: systematic review and meta-analysis
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Abstract<p> Background Rectal cancer is one of the most common malignant tumors of gastrointestinal tract. Combining chemotherapy with radiotherapy has a sound effect on its management.</p><p> Objectives Assessment the patterns of characterizations of rectal cancer. Evaluation of the efficacy, and long-term survival of pre-/ postoperative chemoradiation. Collecting all eligible evidence articles and summarize the results.</p><p> Methods By this systematic review and meta-analysis study, we include data of chemoradiation of rectal cancer articles from 2015 until 2019. The research was carried out at Baghdad Medical City oncology centers. Accordance with the</p> ... Show More
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Publication Date
Fri Mar 01 2024
Journal Name
Baghdad Science Journal
Exploring the Challenges of Diagnosing Thyroid Disease with Imbalanced Data and Machine Learning: A Systematic Literature Review
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Thyroid disease is a common disease affecting millions worldwide. Early diagnosis and treatment of thyroid disease can help prevent more serious complications and improve long-term health outcomes. However, thyroid disease diagnosis can be challenging due to its variable symptoms and limited diagnostic tests. By processing enormous amounts of data and seeing trends that may not be immediately evident to human doctors, Machine Learning (ML) algorithms may be capable of increasing the accuracy with which thyroid disease is diagnosed. This study seeks to discover the most recent ML-based and data-driven developments and strategies for diagnosing thyroid disease while considering the challenges associated with imbalanced data in thyroid dise

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Publication Date
Mon Aug 02 2021
Journal Name
International Journal Of Dental Hygiene
Efficacy of erythritol powder air‐polishing in active and supportive periodontal therapy: A systematic review and meta‐analysis
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Abstract<sec><title>Objective

This systematic review aimed to analyse available evidence to answer two focused questions about the efficacy of erythritol powder air‐polishing (EPAP) (i) as an adjunctive during active periodontal therapy (APT) and (ii) as an alternative to hand/ultrasonic instrumentation during supportive periodontal therapy (SPT). Additionally, microbiological outcomes and patient's comfort/perceptions were assessed as secondary outcomes.

Methods

PubMed, Cochrane and Medline were searched for relevant articles published before February 2021 following PRISMA guidelines. The search was conducted by three indep

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Publication Date
Mon Feb 01 2021
Journal Name
Meta Gene
Association analysis of FTO gene polymorphisms rs9939609 and obesity risk among the adults: A systematic review and meta-analysis
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