Active learning of an action detector on untrimmed videos

textCollecting and annotating videos of realistic human actions is tedious, yet critical for training action recognition systems. We propose a method to actively request the most useful video annotations among a large set of unlabeled videos. Predicting the utility of annotating unlabeled video is not trivial, since any given clip may contain multiple actions of interest, and it need not be trimmed to temporal regions of interest. To deal with this problem, we propose a detection-based active learner to train action category models. We develop a voting-based framework to localize likely intervals of interest in an unlabeled clip, and use them to estimate the total reduction in uncertainty that annotating that clip would yield. On three datasets, we show our approach can learn accurate action detectors more efficiently than alternative active learning strategies that fail to accommodate the "untrimmed" nature of real video data.Computer Science

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A Study of the Rheological Properties and Gluten Protein Components Associated with Enhanced Baking Quality in Durum Wheat (Triticum turgidum L. var. durum)

Durum wheat (Triticum turgidum L. var. durum, 2n = 4x = 28, AABB genomes) is used predominantly for semolina and pasta products, but there is increasing interest in using durum for bread-making to provide alternative markets during periods of overproduction. The goal of this study was to characterize the bread-making quality of durum wheat cultivars and emmer (Triticum turgidum L. var. dicoccum, 2n = 4x = 28) derived breeding lines derived from crosses of durum wheat with an Emmer land race ‘97Emmer19’ from Iran. Emmer-derived breeding lines were evaluated along with three high quality bread wheat (Triticum aestivum L., 2n = 6x = 42, AABBDD genomes) cultivars and seven durum wheat cultivars across three environments in replicated yield trials in the 2005 and 2006 growing seasons. Four 1AS.1AL-1DL translocation lines which carry the Glu-D1d allele [high molecular weight glutenin subunit (HMW-GS) pair 1Dx5+1Dy10] from chromosome 1D of bread wheat were also evaluated. In general, durum wheat cultivars with elevated gluten strength and/or increased dough extensibility were noted to have higher loaf volume (LV) than those with weaker gluten. The 1AS.1AL-1DL translocation line ‘L252’ carrying the LMW-1 banding pattern had better dough mixing stability and LV than the translocation lines with the LMW-2 banding pattern. The 1AS.1AL-1DL translocation lines had higher grain protein concentrations (GPC), but the lowest loaf volumes of all the lines tested. These translocation lines also exhibited unappealing external loaf quality (loaf shape and appearance) and poor internal loaf quality (crumb structure). Variation in bread-making quality attributes were observed among durum genotypes. ‘97Emmer19’ exhibited higher LV than all the durum wheats evaluated and approached the loaf volume achieved with the bread wheat cultivar ‘AC Superb’. Breeding lines derived from crosses of ‘97Emmer19’ to strong gluten durum cultivars (‘WB881’ or ‘AC Navigator’) had higher LV than those of the durum checks. ‘97Emmer19’ carried Glu-A1a* (HMW-GS 1Ax1) and the progeny carrying that allele generally exhibited higher loaf volumes. Durum wheat genotypes expressing the Glu-B1d (HMW-GS pair Bx6+By8) allele exhibited better overall bread-making quality compared with those expressing the Glu-B1b (HMW-GS pair Bx7+By8) allele. The durum cultivar ‘Arcola’ and the emmer-derived breeding line ‘2000EB4’, showed higher alveograph extensibility (L) values than did the bread wheat check ‘AC Barrie’. The durum wheat genotypes (with the exception of ‘Stewart-63’) and emmer-derived breeding lines exhibited better dough extensibility than the USDA-ARS 1AS.1AL-1DL translocation lines. These results indicate that there is potential to select for genotypes with improved baking quality in durum breeding programs

NEW STABILITY-INDICATING ULTRA PERFORMANCE LIQUID CHROMATOGRAPHY METHOD DEVELOPMENT AND VALIDATION OF LENVATINIB MESYLATE IN BULK DRUG AND PHARMACEUTICAL DOSAGE FORMS

Objective: The objective of the present study was to develop and validate a new stability-indicating method for the quantification of lenvatinib mesylate in bulk drug and pharmaceutical dosage form using ultra performance liquid chromatography (UPLC).Methods: The optimized chromatographic conditions for elution of drug included UPLC HSS C18 (100 mm × 2.1 mm, 1.8 m) column, mixture of 0.1% orthophosphoric acid and acetonitrile (50:50 v/v%) mobile phase run on an isocratic mode at a flow rate of 0.3 mL/min, 240 nm detection wavelength, and column oven temperature maintained at 30°C.Results: The retention time for lenvatinib was found to be 1.24 min. The developed method was validated for various validation parameters in accordance with the International Conference on Harmonization guidelines. The method obeyed Beer's law in the concentration range of 2.5– 15 μg/mL with a correlation coefficient of 0.9996. The percentage relative standard deviation and percentage recovery were determined to be 0.4 and 99.66–100.30%, respectively. The developed method was found to be accurate, precise, specific, linear, rugged, and robust. Forced degradation studies were conducted by exposing the drug to diverse stress conditions such as acidic, basic, peroxide, neutral, photolytic, and thermal conditions. The net degradation was obtained within the limits.Conclusion: The developed method for the estimation of lenvatinib can be employed to routine analysis of pharmaceutical dosage form

Stability indicating RP-HPLC method development and validation for the simultaneous determination of Sofosbuvir and Velpatasvir in tablet dosage forms

Stability indicating RP-HPLC method was developed for the simultaneous quantitation of Sofosbuvir and Velpatasvir in its pharmaceutical dosage form and validated. The drugs were separated on Discovery C18 (150mm x 4.6mm, 5μ) column using 0.01N potassium dihydrogen phosphate buffer and acetonitrile (50:50%v/v) as mobile phase on isocratic mode. The mobile phase is pump into the column at flow rate of 1.0ml/min and column oven temperature is maintained at 30ºC. The drugs were detected at a wavelength 240nm. The retention time for Sofosbuvir and Velpatasvir were found to be 2.32min and 3.34min respectively. The developed method is validated in accordance with ICH guidelines. The method was found to be accurate, precise, specific and robust. The method obeys Beer’s law at a concentration range of 100μg/ml – 600μg/ml of Sofosbuvir and 25μg/ml – 150μg/ml of Velpatasvir, with correlation coefficient of 0.999 for both the drugs. The drugs were found to be stable and less prone to degradation when they are subjected to various stress conditions

Scaling up graphene PET nano-composites for industry applications

Graphene nanocomposites have offered promise to benefit manufactured goods and their packaging materials for over a decade. The promise includes improving thermal properties for processing, increased specific strength, enhanced barrier properties, and electrical conductivity. Often such improvements have a potential for implementation with very little change in industry standard processing equipment. As commodity and energy costs rise, efficient product design becomes increasingly important. Shipping and material costs have risen to a larger, and often leading, fraction of manufacturer’s total costs. Simply using less material means less weight, which both reduces raw material and transportation costs. However, this is only possible if the new design performance meets or exceeds market needs. An additional benefit of material reduction is a reduced impact on the environment. Some specific examples of environmental impact reduction from the use of graphene based nanocomposites were recently measured at 30%. In that case, the thermal properties provided the most significant benefit, allowing processing using less energy. There also appears to be benefit in recycling graphene-PET nano-composites over other additives in the recycle stream. Mechanical property enhancement from graphene nanocomposites remains the most important benefit for manufacturing. The promise of graphene nanocomposites to provide the lightweight high performance alternative to 20th century materials still stands. However, adaptation of nanocomposites in day-to-day applications outside the laboratory at industrial scale are lagging due to limitations with dispersing the nano-phase. A new approach of dosing nano-phase materials dispersed in a liquid medium during industry compatible molding processes can deliver the intended level of property improvements. This new method and resulting property improvements are discussed with examples including: improved thermal conductivity from graphene dispersed through melt mixing and liquid dosing; exfoliated graphene obtained through liquid dispersion improving the elastic modulus without impacting film clarity; and methods to track dosing consistency or quantifying dispersion level. These all indicate an effective exfoliation fraction exists which improves the composite properties

A DDoS Attack Detection using PCA Dimensionality Reduction and Support Vector Machine

Distributed denial-of-service attack (DDoS) is one of the most frequently occurring network attacks. Because of rapid growth in the communication and computer technology, the DDoS attacks became severe. So, it is essential to research the detection of a DDoS attack. There are different modes of DDoS attacks because of which a single method cannot provide good security. To overcome this, a DDoS attack detection technique is presented in this paper using machine learning algorithm. The proposed method has two phases, dimensionality reduction and model training for attack detection. The first phase identifies important components from the large proportion of the internet data. These extracted components are used as machine learning’s input features in the phase of model detection. Support Vector Machine (SVM) algorithm is used to train the features and learn the model. The experimental results shows that the proposed method detects DDoS attacks with good accuracy

PET – A semi-crystalline nanocomposite

Polymer nanocomposites sparked significant interest due to unprecedented material properties and property combinations. While most polymer nanocomposites are multi-phase materials with distinctive chemical structure for each phase, it is possible to make a reinforcement with the same chemistry. Such composites have been demonstrated in metals and polymers. Reinforcement with the same base chemistry (self-reinforcing) has advantages in compatibility, load transfer, and processing ability. Composite research continues on interface properties and their optimization. This is often complicated by poor surface chemistry interactions. Polyethylene terephthalate (PET), a widely known semi-crystalline polymer, possess a unique micro-structure that can be engineered through process history. Bi-axial stretching near the glass transition temperature yields a semi-crystalline microstructure in PET controlled by a function of temperature and strain rate where, in many cases, the crystalline phase can be kept small and acts as a nano-scale reinforcement. Please click Additional Files below to see the full abstract