Purification,structural data and biological properties of polysaccharide from Prunus amygdalus gum

This work demonstrates the efficiency of almond gum polysaccharides (AGPs) as bioactive compounds. AGPs were first extracted using H₂O₂, in the presence of NaOH, at different times and temperatures. The optimal extraction conditions were 4% H₂O₂ and 2 N NaOH, for 7 h at 50 °C, leading to an extraction yield of 58.2% (w/w). After a purification step, the retained AGPs were characterised using high‐performance liquid chromatography showing a molecular weight of 99.3 kDa. The monosaccharide composition of AGPs were assessed using gas chromatography–mass spectrometry. AGPs were found to be a complex heteropolysaccharide with a repeating unit mainly composed of galactose, arabinose, xylose, mannose, rhamnose, and glucuronic acid with the respective ratios: 45:26:7:10:1:11. The acidic nature of the polysaccharide is due to the presence of glucuronic acid. Total antioxidant activity, free radical‐scavenging activity and reducing power assay of AGPs were investigated. The obtained results showed high antioxidant activities of AGPs. Furthermore, beyond 60 mg mL^?1, AGPs exhibited bacterial growth inhibition for five pathogenic strains: Escherichia coli, Staphylococcus aureus, Enterococcus feacalis, Pseudomonas aeruginosa and Salmonella typhimurium.     

New pulse mode neuro-fuzzy hardware architecture and application to image denoising

This paper focuses on a new digital architecture of pulse mode neuro-fuzzy system (PMNFS) with on-chip learning ability. The main purpose goal is to make use of the outstanding features of neuro-fuzzy in function approximation, and implement a reconfigurable architecture with on-chip learning on a field-programmable gate array (FPGA) platform. Details of the whole design with on-chip learning solutions are given. As an application illustrating the efficiency and scalability of the proposed PMNFS, we have considered the approximation of image denoising, which is a very important step in image processing. Experimental results show great efficiency of the proposed method, outperforming other denoising techniques. It was also demonstrated that such a system is strongly adaptive and gives good restored images independently of the kind of noises. Owing to learning, such feature cannot be met with conventional denoising techniques. Design synthesis results on a virtex II PRO FPGA platform are presented. Comparisons with conventional techniques as well as neural ones show higher performances of the designed PMNFS.     

Enhancing speech intelligibility in reverberant spaces by a speech features distributions dependent pre-processing

In this paper, we deal with a pre-processing based on speech envelope modulation for intelligibility enhancement in reverberant large dimension public enclosed spaces. In fact, the blurring effect due to reverberation alters the speech perception in such conditions. This phenomenon results from the masking of consonants by the reverberated tails of the previous vowels. This is particularly accentuated for elderly persons suffering from presbycusis. The proposed pre-processing is inspired from the steady-state suppression technique which consists in the detection of the steady-state portions of speech and the multiplication of their waveforms with an attenuation coefficient in order to decrease their masking effect. While the steady-state suppression technique is performed in the frequency domain, the pre-processing described in this paper is rather performed in the temporal domain. Its key novelty consists in the detection of the speech voiced segments using a priori knowledge about the distributions of the powers and the durations of voiced and unvoiced phonemes. The performances of this pre-processing are evaluated with an objective criterion and with subjective listening tests involving normal hearing persons and using a set of nonsense Vowel–Consonant–Vowel syllables and railway station vocal announcements.     

Experimental analysis,hybridization and exergetic investigation of an absorption refrigeration unit

In this work, an experimental and theoretical investigation of a frozen and hot water production unit with direct gas absorption is developed. Water/ammonia couple is used.A particular interest is given to the system performances evaluation such as exergetic efficiency and total exergy loss. Parameters analyzed are coefficients of performance, irreversibility and exergetic efficiency.Results show that the machine can reach a COP up to 65% and exergetic efficiency up to 18% for a working temperature and a condensation temperature of 120 °C and 18 °C, respectively. These performances decrease for a condensation temperature of 37 °C and 47 °C. Indeed, the engine is less efficient and presents more irreversibility, which is major in the pre-absorber and the absorber.An improvement of the machine cycle is proposed, in order to adapt it to low grade heat sources, using a compressor upstream of the pre-absorber. Performances of the new hybrid cycle are better than those of the real cycle.     

An efficient microcalcifications detection based on dual spatial/spectral processing

Microcalcifications are tiny deposits of calcium located in breast tissue. They appeared as very small highlighted regions in comparison with their surrounding tissue. Spatial non linear enhancement can be applied for microcalcification detection. However, efficiency of a such approach depends on breast density: in case of extreme breast density, the contrast between microcalcification’s details and their surrounding tissue is attenuated leading to a limitation of spatially based approaches. In that case, frequency analysis such as wavelet based analysis can be more relevant for dissociating microcalcifications. The main goal of Computer Aided Detection systems (CAD) is to detect breast cancer at an early stage for all breast density classes by using entropies to enhance and then detect microcalcification details. Accordingly, we combine our approach a spatial Automatic Non Linear Stretching (ANLS) and Shannon Entropy based Wavelet Coefficient Thresholding (SE_WCT). Validation of the proposed approach is done on the Mammographic Image Analysis Society (MIAS) database. The evaluation of the contrast is based on the Second-Derivative-Like measure of enhancement(SDME). Accordingly, it yields to a mean SDME of 78.8dB on the whole database. The performance metric for evaluating our proposed CAD is the Receiver Operating Characteristic(ROC) curve and the free-response ROC (FROC). An area under the ROC curve A _z = 0.92 is obtained as well as 97.14 % of True Positives (TP) with 0,48 False positives per image (FP).