Movies Tags Extraction Using Deep Learning

Retrieving information from movies is becoming increasingly demanding due to the enormous amount of multimedia data generated each day. Not only it helps in efficient search, archiving and classification of movies, but is also instrumental in content censorship and recommendation systems. Extracting key information from a movie and summarizing it in a few tags which best describe the movie presents a dedicated challenge and requires an intelligent approach to automatically analyze the movie. In this paper, we formulate movies tags extraction problem as a machine learning classification problem and train a Convolution Neural Network (CNN) on a carefully constructed tag vocabulary. Our proposed technique first extracts key frames from a movie and applies the trained classifier on the key frames. The predictions from the classifier are assigned scores and are filtered based on their relative strengths to generate a compact set of most relevant key tags. We performed a rigorous subjective evaluation of our proposed technique for a wide variety of movies with different experiments. The evaluation results presented in this paper demonstrate that our proposed approach can efficiently extract the key tags of a movie with a good accuracy

Spatial and temporal assessment of groundwater recharge in the Fordwah Eastern Sadiqia (South) Project area

Irrigation programs / Drainage / Groundwater / Monitoring / Recharge / Aquifers / Water table / Irrigation systems / Irrigation canals / Waterlogging / Pakistan / Indus Basin / Fordwah Eastern Sadiqia

A multivariate method to determine the dimensionality of neural representation from population activity.

How do populations of neurons represent a variable of interest? The notion of feature spaces is a useful concept to approach this question: According to this model, the activation patterns across a neuronal population are composed of different pattern components. The strength of each of these components varies with one latent feature, which together are the dimensions along which the population represents the variable. Here we propose a new method to determine the number of feature dimensions that best describes the activation patterns. The method is based on Gaussian linear classifiers that use only the first d most important pattern dimensions. Using cross-validation, we can identify the classifier that best matches the dimensionality of the neuronal representation. We test this method on two datasets of motor cortical activation patterns measured with functional magnetic resonance imaging (fMRI), during (i) simultaneous presses of all fingers of a hand at different force levels and (ii) presses of different individual fingers at a single force level. As expected, the new method shows that the representation of force is low-dimensional; the neural activation for different force levels is scaled versions of each other. In comparison, individual finger presses are represented in a full, four-dimensional feature space. The approach can be used to determine an important characteristic of neuronal population codes without knowing the form of the underlying features. It therefore provides a novel tool in the building of quantitative models of neuronal population activity as measured with fMRI or other approaches

Drastic impacts of 8th October earthquake in Kashmir and role of sustainable development

The main environmental loses from the earthquake to the environment were the heavy landslides, destruction of residential and commercial structures, destruction and rerouting of water bodies, etc. Due to the lack of sustainable planning and awareness, debris, building waste materials and misuse of other materials are seriously spoiling the sustainability of the area. Detail survey of the ruined areas of Kashmir due to 8th October earthquake after five years has been performed during this research. Present conditions of the study area are presenting the worst picture. Improper management of dumped construction waste is one of the serious issues. Environmental and sustainability conditions before and after earthquake are compared in this research work. It is concluded that infrastructure development and building construction during last five years after the earthquake are not fulfilling the sustainability requirement. Proper waste handing, recycling of materials, promotion of indigenous building materials and awareness among the local dwellers may help to improve the sustainability and environmental conditions in the study area

Video Summarization Using Deep Semantic Features

Computer Vision - ACCV 2016: 13th Asian Conference on Computer Vision, Nov 20-24, 2016, Taipei, TaiwanThis paper presents a video summarization technique for an Internet video to provide a quick way to overview its content. This is a challenging problem because finding important or informative parts of the original video requires to understand its content. Furthermore the content of Internet videos is very diverse, ranging from home videos to documentaries, which makes video summarization much more tough as prior knowledge is almost not available. To tackle this problem, we propose to use deep video features that can encode various levels of content semantics, including objects, actions, and scenes, improving the efficiency of standard video summarization techniques. For this, we design a deep neural network that maps videos as well as descriptions to a common semantic space and jointly trained it with associated pairs of videos and descriptions. To generate a video summary, we extract the deep features from each segment of the original video and apply a clustering-based summarization technique to them. We evaluate our video summaries using the SumMe dataset as well as baseline approaches. The results demonstrated the advantages of incorporating our deep semantic features in a video summarization technique

Comparing the efficacy and safety of faecal microbiota transplantation with bezlotoxumab in reducing the risk of recurrent Clostridium difficile infections:a systematic review and Bayesian network meta-analysis of randomised controlled trials

The risk of recurrent Clostridium difficile infections (RCDIs) is high when treated with standard antibiotics therapy (SAT) alone. It is suggested that the addition of faecal microbiota transplantation (FMT) or bezlotoxumab after SAT reduces the risk of RCDI. In the absence of head-to-head randomised controlled trials (RCTs), this review attempts to compare the efficacy and safety of bezlotoxumab with FMT in reducing the risk of RCDI in hospitalised patients.Open access journalThis item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]

Antibacterial efficacy of indigenous Pakistani honey against extensively drug-resistant clinical isolates of Salmonella enterica serovar Typhi: an alternative option to combat antimicrobial resistance

Abstract Background Extensively drug-resistant (XDR) Salmonella enterica serovar Typhi (S. Typhi) poses a grave threat to public health due to increased mortality and morbidity caused by typhoid fever. Honey is a promising antibacterial agent, and we aimed to determine the antibacterial activity of honey against XDR S. Typhi. Methods We isolated 20 clinical isolates of XDR S. Typhi from pediatric septicemic patients and determined the minimum inhibitory concentrations (MICs) of diferent antibiotics against the pathogens using the VITEK 2 Compact system. Antimicrobial-resistant genes carried by the isolates were identifed using PCR. The antibacterial efcacy of fve Pakistani honeys was examined using agar well difusion assay, and their MICs and minimum bactericidal concentrations (MBCs) were determined with the broth microdilution method. Results All 20 isolates were confrmed as S. Typhi. The antibiogram phenotype was confrmed as XDR S. Typhi with resistance to ampicillin (≥32 µg/mL), ciprofoxacin (≥4 µg/mL), and ceftriaxone (≥4 µg/mL) and sensitivity to azithromycin (≤16 µg/mL) and carbapenems (≤1 µg/mL). Molecular conformation revealed the presence of blaTM-1, Sul1, qnrS, gyrA, gyrB, and blaCTX-M-15 genes in all isolates. Among the fve honeys, beri honey had the highest zone of inhibition of 7–15 mm and neem honey had a zone of inhibition of 7–12 mm. The MIC and MBC of beri honey against 3/20 (15%) XDR S. Typhi isolates were 3.125 and 6.25%, respectively, while the MIC and MBC of neem were 3.125 and 6.25%, respectively, against 3/20 (15%) isolates and 6.25 and 12.5%, respectively, against 7/20 (35%) isolates. Conclusion Indigenous honeys have an efective role in combating XDR S. Typhi. They are potential candidates for clinical trials as alternative therapeutic options against XDR S. Typhi isolates. Keywords Antimicrobial resistance, Natural antibiotics, XDR S. Typhi, MIC, Honey, Resistance gene

Supplementing a-Linolenic acid in the in vitro maturation media improves nuclear maturation rate of oocytes and early embryonic development in the Nili Ravi buffalo

The present study was conducted to investigate the effect of omega-3 poly unsaturated fatty acid (PUFA), α-linolenic acid (ALA; 18:3 n-3) on the in vitro maturation (IVM) of buffalo oocytes and subsequent embryonic development. Buffalo cumulusoocyte complexes (COCs; n = 2282) were in vitro matured in TCM-199 (0.6% fatty acid free bovine serum albumin, 0.02 Units/ml FSH, 1 µg/ml 17-β-estradiol, 10 µg/ml epidermal growth factor, 50 µg/ml gentamicin) supplemented with 0 (control), 25, 50, 100, 150 or 300 µm ALA under an atmosphere of 5% CO2 in air at 38.5ºC for 22-24 h. The matured oocytes were then fertilized in Tyrode’s Albumin Lactate Pyruvate (TALP) medium and cultured in synthetic oviductal fluid (SOF) medium. Concentrations up to 100 μm ALA improves (P ≤ 0.05) the cumulus expansion compared to control. Higher percentage of oocytes reaching MII stage was observed at 50 μm and 100 μm of ALA compared to control (P ≤ 0.05). Concentrations of 150 and 300 µm ALA were detrimental both for cumulus expansion and nuclear maturation rate of buffalo oocytes. Moreover, supplementation with 100 μm ALA improved (P ≤ 0.05) cleavage rate compared to control and treatment with 50 and 100 μm ALA yielded significantly higher morulae compared to control. The results of present study indicate that the supplementation with 100 μm ALA to the IVM medium improves nuclear maturation rate of buffalo oocytes and subsequent early embryonic development

Low Resistance Polycrystalline Diamond Thin Films Deposited by Hot Filament Chemical Vapour Deposition

Polycrystalline diamond thin films with outgrowing diamond (OGD) grains were deposited onto silicon wafers using a hydrocarbon gas (CH4) highly diluted with H2 at low pressure in a hot filament chemical vapour deposition (HFCVD) reactor with a range of gas flow rates. X-ray diffraction (XRD) and SEM showed polycrystalline diamond structure with a random orientation. Polycrystalline diamond films with various textures were grown and (111) facets were dominant with sharp grain boundaries. Outgrowth was observed in flowerish character at high gas flow rates. Isolated single crystals with little openings appeared at various stages at low gas flow rates. Thus, changing gas flow rates had a beneficial influence on the grain size, growth rate and electrical resistivity. CVD diamond films gave an excellent performance for medium film thickness with relatively low electrical resistivity and making them potentially useful in many industrial applications