Human activity recognition with different artificial neural network based classifiers [Farkli Yapay Sinir Aǧi Temelli Siniflandiricilar ile İnsan Hareketi Tanimlama]

Human Activity Recognition is a popular topic of research, with the importance it carries and its limited feature vector, to reach high success rates because of the difficulty faced in classification. With the increase of movement measurability for individuals via inertia measuring units embedded inside the smartphones, the data amount increases which lets new classifiers to be designed with higher success in this field. Artificial neural networks can perform better at such classification problems in comparison to conventional classifiers. In this work, various artificial neural networks have been tried to form a classifier for the University of California (UCI) Human Activity Recognition dataset and resulting success rates for those classifiers are compared with existing results for same dataset in the literature. © 2017 IEEE

A comparative study of classification methods for fall detection [Düşme tespiti için siniflandirma yöntemlerinin karşilaştirilmasi]

A comparative study of various fall detection algorithms based upon measurements of a wearable tri-axial accelerometer unit is presented in this paper. Least squares support vector machine, neural network and rule-based classifiers are evaluated in the scope of this paper. Training and testing data sets, which are necessary for design and testing of the classifiers, respectively, are collected from 7 people. Each subject exercised simulated falls and other daily life activities such as walking, sitting etc. Among three methods, support vector machine-based classifier is found to be superior in terms of both correct detection and false alarm ratio as 87,76% precision and 89.47% specifity. Meanwhile, best sensitivity is achieved with rule-based classifiers. © 2014 IEEE

Does chlorhexidine affect the shear bond strengths of orthodontic brackets?

Background/purpose: The purpose of this study was to examine the effect of 1% chlorhexidine (CHX) gel on the shear bond strength (SBS) of orthodontic brackets bonded with Transbond XT (XT, 3M Unitek) and Transbond Plus Self-Etching Primer (TSEP, 3M Unitek). Materials and methods: In total, 75 extracted premolars were collected and randomly divided into five groups of 15 teeth each. Brackets were bonded to teeth using a different experimental technique for each group as follows: (I) (control): etch/dry/Transbond XT; (II) CHX gel/etch/dry/Transbond XT; (III) etch/dry/CHX gel/Transbond XT; (IV) dry/TSEP; and (V) CHX gel/dry/TSEP. All products were used according to the manufacturers' instructions. An Instron Universal Testing Machine was used to directly apply an occlusal shear force onto the enamel-bracket interface at a speed of 0.5 mm/min. Residual adhesive on each tooth was evaluated using an adhesive remnant index (ARI). Analysis of variance was used to compare the SBS of the groups, and a Chi-squared test was used to compare ARI scores. Results: Group I had the highest mean SBS (16.47 ± 4.2 MPa), followed by Groups II (16.24 ± 4.5 MPa), III (13.08 ± 4.50 MPa), IV (11.95 ± 2.7 MPa) and V (11.16 ± 2.8 MPa). No statistical differences were observed between Groups I and II (P > 0.05) or between groups IV and V (P > 0.05). However, SBS scores for Groups IV and V were significantly lower than those of Groups I and II (P > 0.05). No significant difference was observed in ARI scores among any of the groups (P > 0.05). Prior application of CHX gel did not significantly affect the SBS of orthodontic bonding adhesives. © 2011, Association for Dental Sciences of the Republic of China

Antibacterial Effects of Several Current Orthodontic Materials against Streptococcus mutans

KAMAK, HASAN/0000-0003-1910-3694WOS: 000322424100010PubMed: 23757904The aim of this study was to examine the antibacterial effect of several current orthodontic materials against a certain oral bacterium. The antibacterial activities of six orthodontic composite resins (Transbond LR, Light Cure Retainer (LCR), Light Bond, System 1+, Kurasper E Transbond XT adhesive), two orthodontic bonding materials (Transbond XT primer and System 1+ activator) and two glass ionomer cements (GIC) [Multicure Glass Ionomer and Ketac Cem WC] were evaluated against Streptococcus mutans. The hard materials were put into the Teflon mould. The liquid materials were put on a paper disc. All materials were handled under aseptic conditions and placed on agar culture plates. All plates were incubated at 5% CO2 and 37 degrees C for 48 hours. The bacterial growth inhibition zones including the diameter of the sample were measured in millimetres. As a result of this study, the multicure GIC showed the highest antibacterial effectiveness, but no inhibition zones were noted for ketac cem GIC. The light bond adhesive of the Reliance orthodontic bonding system produced high antibacterial effect against S mutans, while the Reliance composite (LCR) did not show any antibacterial effect (p < 0.05). Both composite and primer of the transbond XT system demonstrated significant antibacterial effect against the test bacterium when compared to transbond LR (p < 0.05). Among the materials tested, kurasper F, Ormco system 1+ and system 1+ activator showed slight or no inhibitory effect against the test bacterium in this study. In patients who have relatively high salivary levels of Streptococci mutans before treatment, the multicure GIG, the Reliance light bond adhesive, and transbond XT system which had high level antibacterial properties could be applied