Objectives: To review the failure rates of molar tubes and the effect of molar tube base design, adhesive type, and bonding technique on the failure rates of molar tubes. Data: The revolution of molar bonding greatly impacted fixed orthodontic appliance treatment by reducing chair-side time and improving patient comfort. Even with the many advantages of molar bonding, clinicians sometimes hesitate to use molar tubes due to their failure rates. Sources: Internet sources, such as Pubmed and Google Scholar. Study selection: studies testing the bond failure rate of molar tubes. Conclusions: The failure rate of the molar tubes can be reduced and the bond strength of the molar tubes can be improved by changing the design of the molar tube base

Significant advances in the automated glaucoma detection techniques have been made through the employment of the Machine Learning (ML) and Deep Learning (DL) methods, an overview of which will be provided in this paper. What sets the current literature review apart is its exclusive focus on the aforementioned techniques for glaucoma detection using the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines for filtering the selected papers. To achieve this, an advanced search was conducted in the Scopus database, specifically looking for research papers published in 2023, with the keywords "glaucoma detection", "machine learning", and "deep learning". Among the multiple found papers, the ones focusing

Several Intrusion Detection Systems (IDS) have been proposed in the current decade. Most datasets which associate with intrusion detection dataset suffer from an imbalance class problem. This problem limits the performance of classifier for minority classes. This paper has presented a novel class imbalance processing technology for large scale multiclass dataset, referred to as BMCD. Our algorithm is based on adapting the Synthetic Minority Over-Sampling Technique (SMOTE) with multiclass dataset to improve the detection rate of minority classes while ensuring efficiency. In this work we have been combined five individual CICIDS2017 dataset to create one multiclass dataset which contains several types of attacks. To prove the eff

The basic solution to overcome difficult issues related to huge size of digital images is to recruited image compression techniques to reduce images size for efficient storage and fast transmission. In this paper, a new scheme of pixel base technique is proposed for grayscale image compression that implicitly utilize hybrid techniques of spatial modelling base technique of minimum residual along with transformed technique of Discrete Wavelet Transform (DWT) that also impels mixed between lossless and lossy techniques to ensure highly performance in terms of compression ratio and quality. The proposed technique has been applied on a set of standard test images and the results obtained are significantly encourage compared with Joint P

In this study, we have created a new Arabic dataset annotated according to Ekman’s basic emotions (Anger, Disgust, Fear, Happiness, Sadness and Surprise). This dataset is composed from Facebook posts written in the Iraqi dialect. We evaluated the quality of this dataset using four external judges which resulted in an average inter-annotation agreement of 0.751. Then we explored six different supervised machine learning methods to test the new dataset. We used Weka standard classifiers ZeroR, J48, Naïve Bayes, Multinomial Naïve Bayes for Text, and SMO. We also used a further compression-based classifier called PPM not included in Weka. Our study reveals that the PPM classifier significantly outperforms other classifiers such as SVM and N

This paper explores VANET topics: architecture, characteristics, security, routing protocols, applications, simulators, and 5G integration. We update, edit, and summarize some of the published data as we analyze each notion. For ease of comprehension and clarity, we give part of the data as tables and figures. This survey also raises issues for potential future research topics, such as how to integrate VANET with a 5G cellular network and how to use trust mechanisms to enhance security, scalability, effectiveness, and other VANET features and services. In short, this review may aid academics and developers in choosing the key VANET characteristics for their objectives in a single document.

In this study, the concentration of radium and uranium in the samples radish leaves, radish stalk, onion leaves, onion stalk and garlic fruits were grown in arable soil in the Botanical Garden in the College of Science for women, and garlic in special plates, the soil was taken from the above at the beginning of November 2016 was studied by using CR-39 nuclear track detectors. The radium and uranium concentration varied from 0.023 to 0.052 and from 23.13 to 52.68 Bq/kg with an average value of 0.037 and 37.58 Bq/kg respectively. The maximum value of radon concentration was 0.052 Bq/kg in fruits of garlic sample, while the minimum value was 0.023 Bq/kg in radish leaves. The values of the radium and uranium concentrations obtained from this s

This study has been conducted to know the level of microbial ( bacteria and fungi) contamination in 5 types of biscuits from local markets of Baghdad city. Fifty samples (ten sample for each kind of biscuit) were studed,Two are local,others are Iranian,Turkish,and Holandies. The following results have been achieved :1. The highest number of bacteria was 21.6×103 cell/g in Iranian biscuit while the lowest number was 14.3× 103 cell/g in local biscuit No.1 . The highest number of fungi was 16×103 colony/g and the lowest number was 5.3×103 colony/g in the Iranian and the local biscuit No.1,respectively.2. Staphylococcus aureus was the major bacteria appeared at highest level of 100% in Turkish biscuit. The lowest percentage was found in H