Multimedia data mining: state of the art and challenges

Advances in multimedia data acquisition and storage technology have led to the growth of very large multimedia databases. Analyzing this huge amount of multimedia data to discover useful knowledge is a challenging problem. This challenge has opened the opportunity for research in Multimedia Data Mining (MDM). Multimedia data mining can be defined as the process of finding interesting patterns from media data such as audio, video, image and text that are not ordinarily accessible by basic queries and associated results. The motivation for doing MDM is to use the discovered patterns to improve decision making. MDM has therefore attracted significant research efforts in developing methods and tools to organize, manage, search and perform domain specific tasks for data from domains such as surveillance, meetings, broadcast news, sports, archives, movies, medical data, as well as personal and online media collections. This paper presents a survey on the problems and solutions in Multimedia Data Mining, approached from the following angles: feature extraction, transformation and representation techniques, data mining techniques, and current multimedia data mining systems in various application domains. We discuss main aspects of feature extraction, transformation and representation techniques. These aspects are: level of feature extraction, feature fusion, features synchronization, feature correlation discovery and accurate representation of multimedia data. Comparison of MDM techniques with state of the art video processing, audio processing and image processing techniques is also provided. Similarly, we compare MDM techniques with the state of the art data mining techniques involving clustering, classification, sequence pattern mining, association rule mining and visualization. We review current multimedia data mining systems in detail, grouping them according to problem formulations and approaches. The review includes supervised and unsupervised discovery of events and actions from one or more continuous sequences. We also do a detailed analysis to understand what has been achieved and what are the remaining gaps where future research efforts could be focussed. We then conclude this survey with a look at open research directions.     

MULTI-WALL CARBON NANOTUBE-BASED DNA NANOSENSOR FOR DETERMINING MITOXANTRONE-DNA INTERACTION IN-VITRO

The present study involves the development of a carbon nanotube based DNA nanosensor to determine the toxicological behavior of mitoxantrone (MTX). Mitoxantrone intercalates with DNA and produces a MTX-DNA adduct, resulting in the blockade of protein synthesis and excessive production of free radicals in the myocardium which eventually leads to cardiac toxicity. So, our work employs a DNA nanosensor to investigate the interaction of MTX with DNA. Multi-wall carbon nanotubes (MWCNTs) were functionalized with carboxyl group and were used for immobilization of DNA to construct the DNA nanosensor. The DNA nanosensor was immersed in MTX solution to monitor MTX-DNA interaction with respect to time and alter the resistance of the nanosensor. It was observed that MTX-DNA interaction is fast initially and as time elapses, the change in interaction gets slow due to formation of MTX-DNA adduct. The limit of detection (LOD) and limit of quantification (LOQ) were found as 150 (ng/mL) and 456 (ng/mL), respectively, for DNA nanosensor. This study suggests that the potentiometric nanosensor allows real-time monitoring of the drug-DNA interaction changes by measuring the potential at DNA/sensor interface which can prove to be an important tool in drug discovery pipelines and molecular toxicology.     

Mg-substituted ZnNb2O6-TiO2 composite ceramics for RF/microwaves ceramic capacitors

Microstructure and microwave dielectric properties of Mg-substituted ZnNb₂O₆-TiO₂ microwave ceramics were investigated. Mg acted as a grain refining reagent and columbite phase stabilization reagent. With an increasing Mg content, the amount of ixiolite (Zn, Mg) TiNb₂O₈ decreased, and the amount of (Zn_0.9Mg_0.1)_0.17Nb_0.33Ti_0.5O₂ and columbite increased. ZnO-Nb₂O₅-1.75TiO₂-5 mol.%MgO exhibited excellent dielectric properties (at 950 °C): ?_r = 35.6, Q × f = 16,000 GHz (at 5.6 GHz) and τ_f = −10 ppm/°C. The material was applied successfully to make RF/microwaves ceramic capacitor, whose self-resonance frequency was 19 GHz at low capacitance of 0.13 pF.     

Frequency distributions and spatially dependent variability of ammonium and nitrate concentrations in soil under grazed and ungrazed grassland

The frequency distributions of soil NO ₃ ^- and NH ₄ ⁺ concentrations under grazed and ungrazed grassland were found to be lognormal, irrespective of time of year or soil depth. The variance and skewness of the sample values increased with stocking density and use of N fertilizer. An analysis of the spatial dependence of the variability using the semivariogram showed a high nugget variance, even when three sample values from each sampling point were averaged. Most of the variance was therefore short-range (occurring within a distance of 0.4 m), suggesting that the sample volume for soil mineral N measurement should be as large as is practicably possible. As an estimate of the average mineral N content, the geometric mean of the sample values consistently underestimated the true arithmetic mean of the population from which the same was drawn. The conventional estimate of the arithmetic mean for lognormally distributed samples values was satisfactory when the sample number was > 50 and the (log) variance < 0.75 (µg N cm^–3). However, for data with larger variances, high coefficients of skewness and fewer observations, Sichel's estimator was a more efficient measure of the true population mean.