Synthetic aperture radar imaging with fractional Fourier transform and channel equalization

This paper investigates the Range-Doppler Algorithm based on the Fractional Fourier Transform (RDA-FrFT) to obtain High-Resolution (HR) images for targets in Synthetic Aperture Radar (SAR) imaging. A mathematical framework for the RDA-FrFT is developed in this paper with closed-form expressions for the range and azimuth compression. The channel effect is considered in this paper for the first time with three inverse techniques to reduce this effect; inverse filter deconvolution, Linear Minimum Mean Square Error (LMMSE) deconvolution, and regularized deconvolution. The performance of the RDA-FrFT is compared with the classical RDA, which is based on the Fourier Transform (FT). Simulation results reveal that the RDA-FrFT offers better focusing capabilities and greater side-lobe reduction ratios. The reflectivity profile obtained with the RDA-FrFT demonstrates a superior performance to the classical RDA. Results show also that the RDA-FrFT gives low Peak Side-Lobe (PSL) and Integrated Side-Lobe (ISL) levels after range and azimuth compression for the detected targets. Finally, the results reveal that the proposed regularized deconvolution technique enhances the performance of the RDA-FrFT significantly if the channel effect is considered.     

Wavelet based sub-band parameters for classification of unaspirated Hindi stop consonants in initial position of CV syllables

This paper proposes a new feature extraction technique using wavelet based sub-band parameters (WBSP) for classification of unaspirated Hindi stop consonants. The extracted acoustic parameters show marked deviation from the values reported for English and other languages, Hindi having distinguishing manner based features. Since acoustic parameters are difficult to be extracted automatically for speech recognition. Mel Frequency Cepstral Coefficient (MFCC) based features are usually used. MFCC are based on short time Fourier transform (STFT) which assumes the speech signal to be stationary over a short period. This assumption is specifically violated in case of stop consonants. In WBSP, from acoustic study, the features derived from CV syllables have different weighting factors with the middle segment having the maximum. The wavelet transform has been applied to splitting of signal into 8 sub-bands of different bandwidths and the variation of energy in different sub-bands is also taken into account. WBSP gives improved classification scores. The number of filters used (8) for feature extraction in WBSP is less compared to the number (24) used for MFCC. Its classification performance has been compared with four other techniques using linear classifier. Further, Principal components analysis (PCA) has also been applied to reduce dimensionality.     

Automated interpretation and accessible presentation of technical diagrams for blind people

The EU-supported TeDUB (Technical Drawings Understanding for the Blind) project is developing a software system that aims to make technical diagrams accessible to blind and visually impaired people. It consists of two separate modules: one that analyses drawings either semi-automatically or automatically, and one that presents the results of this analysis to blind people and allows them to interact with it. The system is capable of analysing and presenting diagrams from a number of formally defined domains. A diagram enters the system as one of two types: first, diagrams contained in bitmap images, which do not explicitly contain the semantic structure of their content and thus have to be interpreted by the system, and second, diagrams obtained in a semantically enriched format that already yields this structure. The TeDUB system provides blind users with an interface to navigate and annotate these diagrams using a number of input and output devices. Extensive user evaluations have been carried out and an overall positive response from the participants has shown the effectiveness of the approach.     

To watch from distance: an interactive film model based on Brechtian film theory

With the emergence of new media, interactive film projects have mainly struggled to resolve the contradiction between dramatic structures and interaction. Dramatic film presents identification with the main character, where the viewer is constantly oppressed by the narrative, and therefore lost in illusion. In this context, when we bring on the scene interaction, the drama apparently starts to lose its power.

In this article, a new interactive film model based on Brechtian film theory is proposed. This model presents a new way of spatiotemporal construction where different audiovisual combinations can be viewed successively, and this way the viewer can actively construct his/her own story. Theoretical framework of the Brechtian interactive film model is supported by an interactive film application, named Academia. The main feature of the model is that, while interaction is very simple, the continuity of the narrative is preserved and the film requiring an intellectual level of interpretation.     

Effect of thermal alkaline pretreatment on the anaerobic digestion of wasted activated sludge

The effect of alkaline pretreatment of waste-activated sludge, using two models to study the sequential hydrolysis rates of suspended (Sanders' surface model) and dissolved (Goel's saturation model) solids, on the mesophilic and thermophilic anaerobic digestion rate is evaluated. The pretreatment, which reduces the size of the solids, increases the reaction rate by increasing the surface area and the specific surface hydrolysis constant (K(SBK)); at thermophilic conditions from 0.45 x 10(-3) kg m(-2) d(-1) for the fresh sludge to 0.74 x 10(-3) kg m(-2) d(-1) for the pretreated sludge and at mesophilic conditions these values are 0.28 x 10(-3) kg m(-2) d(-1) and 0.47 x 10(-3) kg m(-2) d(-1) confirming the usefulness of a pretreatment for solids reduction. But for soluble solids, the thermoalkaline pretreatment decreases the reaction rates by inducing a competitive inhibition on the thermophilic anaerobic digestion rate while in the mesophilic range, a non-competitive inhibition is observed. A mathematical simulation of the consecutive reactions, suspended solids to dissolved solids and to methane in staged anaerobic thermophilic-mesophilic digestion, shows that with 4% suspended solids concentration it is better not to use a thermoalkaline pretreatment because overall solids reduction and total methane production are not as good as without pretreatment.     

Effects of sludge retention time and biosurfactant on the treatment of polyaromatic hydrocarbon (PAH) in a petrochemical industry wastewater

A laboratory-scale aerobic activated sludge reactor (AASR) system was employed to investigate the effects of sludge retention time (SRT) on the removal of three polyaromatic hydrocarbons (PAHs) with low benzene rings [(acenaphthene (ACT), fluorene (FLN) and phenanthrene (PHE)] and six PAHs with high benzene rings [(benzo[b]fluoranthene (BbF), benzo[k]fluoranthene (BkF), benzo[a]pyrene (BaP), indeno[1,2,3-cd]pyrene, dibenz[a,h]anthracene (DahA), benzo[g,h,i]perylene (BghiP)] in the presence of rhamnolipid (RD), emulsan (EM) and surfactine (SR) biosurfactants. This study showed that biosurfactants enhance the PAH biodegradation by increasing the biomass growth. RD exhibits a better performance than the other biosurfactants in the removal of the chemical oxygen demand (COD) and PAHs. At a RD concentration of 15 mg/L aerobic treatment for 25 days, SRT was enough to remove over 95% of total PAHs, and COD(dis). Under the same conditions 75% of COD originating from the inert organics (COD(inert)) and 96% of COD originating from the inert soluble microbial products (COD(imp)) were removed. At 25 days SRT and 15 mg/L RD concentration, about 88% of PAHs were biodegraded by the AASR system, 4% were accumulated in the system, 3% were released in the effluent, and 5% remained in the waste sludge.     

Exposure to dust, endotoxin and airborne microorganisms in wastewater sludge thermal drying units

The objective of this study was to assess workers' exposure to bioaerosols in sludge drying units. Simultaneous collection of inhalable dust and airborne biological agents was carried out using rotating cup samplers (CIP 10, Arelco). Sixteen stationary and 30 personal measurements were performed in three drying plants, during summer and winter. Microbial content of air was characterized by high amounts of Gram-negative bacteria, endotoxin, and thermophilic actinomycetes. High differences between exposure levels were observed with regard to workplaces and tasks. Dryers and conveyors in operation were closed, and the monitoring task in the dryer room was associated with low levels of personal exposure, close to background levels. Conversely, cleaning and maintenance of the dryer and conveyors required the equipment to be opened, giving significantly higher task-based personal exposure levels. The fall of dried sludge into indoor containers resulted in high emission and spreading of dust. Mean personal exposure levels to fungi were moderate or low for all tasks. Based on the results of this study, appropriate means of operational control and personal protection are being developed and implemented on sites.     

Spectrophotometric characterization of human impacted surface waters in the Moselle watershed

In order to characterize the pollution discharged into the Moselle River and some of its tributaries, spectroscopic techniques, namely UV-vis spectroscopy and synchronous fluorescence spectroscopy, have been combined. UV-visible spectra were analysed using the maximum of the second derivative at 225 nm (related to nitrates), the SUVA254 and E2/E3 indices (related to the nature of organic matter). Synchronous fluorescence spectra (delta lambda = 50 nm) presented different shapes depending upon the type of pollution. The pollution results from anthropogenic activities: untreated domestic sewage due to misconnections in a periurban river, effluent from urban WWTPS, agricultural runoff (nitrates) in several streams, discharge from a paper mill (humic-like substances due to wood processing) and from steel mills (PAHs).     

Comparative evaluation of text classification techniques using a large diverse Arabic dataset

A vast amount of valuable human knowledge is recorded in documents. The rapid growth in the number of machine-readable documents for public or private access necessitates the use of automatic text classification. While a lot of effort has been put into Western languages—mostly English—minimal experimentation has been done with Arabic. This paper presents, first, an up-to-date review of the work done in the field of Arabic text classification and, second, a large and diverse dataset that can be used for benchmarking Arabic text classification algorithms. The different techniques derived from the literature review are illustrated by their application to the proposed dataset. The results of various feature selections, weighting methods, and classification algorithms show, on average, the superiority of support vector machine, followed by the decision tree algorithm (C4.5) and Naïve Bayes. The best classification accuracy was 97 % for the Islamic Topics dataset, and the least accurate was 61 % for the Arabic Poems dataset.