In recent years, recognition of text from natural scene image and video frame has got increased attention among the researchers due to its various complexities and challenges. Because of low resolution, blurring effect, complex background, different fonts, color and variant alignment of text within images and video frames, etc., text recognition in such scenario is difficult. Most of the current approaches usually apply a binarization algorithm to convert them into binary images and next OCR is applied to get the recognition result. In this paper, we present a novel approach based on color channel selection for text recognition from scene images and video frames. In the approach, at first, a color channel is automatically selected and then selected color channel is considered for text recognition. Our text recognition framework is based on Hidden Markov Model (HMM) which uses Pyramidal Histogram of Oriented Gradient features extracted from selected color channel. From each sliding window of a color channel our color-channel selection approach analyzes the image properties from the sliding window and then a multi-label Support Vector Machine (SVM) classifier is applied to select the color channel that will provide the best recognition results in the sliding window. This color channel selection for each sliding window has been found to be more fruitful than considering a single color channel for the whole word image. Five different features have been analyzed for multi-label SVM based color channel selection where wavelet transform based feature outperforms others. Our framework of color channel selection is script-independent. It has been tested in English (Roman) and Devanagari (Indic) scripts. We have tested our approach on English datasets (ICDAR 2003, ICDAR 2013 MSRA-TD500, IIIT5K, SVT, YVT) publicly available for both video and scene images. For Devanagari script, we collected our own dataset. The performances obtained from experimental results are encouraging and show the advantage of the proposed method.

Aim To evaluate the effect of intraorifice barriers and bases on the healing of apical periodontitis following root canal treatment in mandibular molars. Methodology A total of 120 permanent mandibular molars with necrotic pulps and periapical radiolucencies (PAI score ≥ 3) were recruited. Root canal treatment was performed in all teeth using a standard protocol, following which they were randomly allocated to one of the three treatment groups: intraorifice barrier group: coronal 3‐mm gutta‐percha was removed and replaced with glass–ionomer cement (GIC) barrier. The floor of the pulp chamber was then sealed with 2‐mm‐thick GIC base followed by final composite resin restoration; base group: received 2‐mm‐thick GIC base before placement of composite resin restoration; and control group: had pulp chamber entirely filled with composite resin only. Follow‐up was done at 3, 6, 9 and 12 months. Combination of clinical and radiographic parameters were used to assess treatment outcome. The data were analysed using Kruskal–Wallis, chi‐square and Wilcoxon signed‐rank tests and logistic regression analysis. Results At the end of 12 months, the base group had the most favourable healing (97.1%), whilst the control group had the least favourable healing (83.8%). The intraorifice barrier group had healing of 92.1%. However, there was no significant difference in healing between groups at the end of the follow‐up period (P > 0.05). Additional subgroup analysis revealed a nonsignificant effect of periodontal status and root filling level on periapical healing. Conclusion The use of an additional barrier under permanent restorations did not significantly improve the outcome of primary root canal treatment in posterior teeth after 12 months. However, its influence in the long term requires further evaluation.

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Biomass has great potential as a clean, renewable feedstock for producing modern energy carriers. Low density biomass, such as rice husk, sawdust, bamboo dust, etc., can provide a continuous supply of liquid and gaseous fuels through thermochemical conversion processes. In the present study, kinetics of the thermal decomposition of three biomasses such as rice husk, sawdust, and bamboo dust were evaluated under air atmosphere from ambient temperature to 1000 °C at a heating rate of 10 °C min−1. Two distinct reaction zones were observed for all the three biomasses. From the thermogravimetric (TG) and differential TG curves, the activation energies, pre-exponential factors, and order of reaction were determined for both the reaction zones. Experimental results were validated numerically and these results are found to be very close to the numerical results. As observed, thermal decomposition rates in the first reaction zone were found to be significantly higher than those in the second reaction zone.

It has now been well established that the depth of bedrock is a key parameter in assessing the impact of local site conditions on seismic hazard analysis. Where conventional geotechnical testing like standard penetration test (SPT) or cone penetration test (CPT) requires a far greater cost and manpower to be used for such purposes, geophysical testing like ground-penetrating radar (GPR) and multichannel analysis of surface waves (MASW) may provide the researchers with more viable options to achieve conclusive evidence on bedrock depth. Application of geophysical techniques has become more and more extensive and advanced in many geo-morphological studies since the early 2000s. Geophysical techniques require less time and effort, and the easy processing of the obtained data is the primary reason for their popularity. However, due to variability in subsoil mechanical properties, wave attenuation and dispersion and diverse geological boundary conditions, the results obtained through geophysical techniques are often ambiguous and non-unique. The interpretation of the obtained data also requires skill and experience, as the range may vary widely and more often than not consensus is difficult to achieve. In this paper, an endeavor has been made to coalesce the results of two widely used geophysical techniques, namely GPR and MASW to derive more conclusive evidence for the detection of bedrock depth in a part of Garhwal Himalayas. The study area comprises of two different cities of Uttarakhand, India. Both the sites possess different geo-morphological attributes and thus prove to be a perfect platform to conduct the experimentations. Both GPR and MASW testing have been performed and results are shown in graphical format. A comparison of the GPR survey with a conventional geotechnical testing (SPT) is also presented here. This study shows that GPR and MASW can provide complementary results in estimating bedrock depth.

Besifloxacin is a unique chiral broad-spectrum flouroquinolone used in the treatment of bacterial conjunctivitis. R-form of besifloxacin hydrochloride shows higher antibacterial activity as compared to the S-isomer. Therefore, it is necessary to establish chiral purity. To establish chiral purity a high-performance liquid chromatography (HPLC) method for determination of R-besifloxacin and S-besifloxacin (BES impurity A) was developed and validated for in-process quality control and stability studies. The analytical performance parameters such as linearity, precision, accuracy, specificity, limit of detection (LOD), and lower limit of quantification (LOQ) were determined according to International Council for Harmonization ICH Q2(R1) guidelines. HPLC separation was achieved on Chiralpak AD-H (250 x 4.6 mm, 5 μm) column using n-heptane: ethanol: ethylenediamine: acetic acid (800:200:0.5:0.5) (v/v/v/v) as the mobile phase in an isocratic elution. The eluents were monitored by UV/Visible detector at 290 nm. The resolution between S-isomer and besifloxacin hydrochloride was more than 2.0. Based on a signal-to-noise ratio of 3 and 10 the LOD of besifloxacin was 0.30 μg/mL, while the LOQ was 0.90 μg/mL. The calibration curves were linear in the range of 0.9-7.5 μg/mL. Precision of the method was established within the acceptable range. The method was suitable for the quality control enantiomeric impurity in besifloxacin hydrochloride. Chirality 28:628-632, 2016. © 2016 Wiley Periodicals, Inc.

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