A Multi-Expert System for chlorine electrolyzer monitoring

The Chlor-Alkali production is one of the largest industrial scale electro-synthesis in the world. Plants with more than 1000 individual reactors are common, where chlorine and hydrogen are only separated by 0.2 mm thin membranes. Wrong operating conditions can cause explosions and highly toxic gas releases, but also irreversible damages of very expensive cell components with dramatic maintenance costs and production loss. In this paper, a Multi-Expert System based on first-order logic rules and Decision Forests is proposed to detect any abnormal operating conditions of membrane cell electrolyzers and to advice the operator accordingly. Robustness to missing data – which represents an important issue in industrial applications in general – is achieved by means of a Dynamic Selection strategy. Experiments performed with real-world electrolyzer data indicate that the proposed system can significantly detect the different operating modes, even in the presence of high levels of missing data – or “wrong” data, as a consequence of maloperation –, which is essential for precise fault detection and advice generation.     

MICROFLORA CHANGES IN TUNA MINCE DURING CONVECTION AIR DRV1NG

Abstract

Microorganisms grow in tuna during drying at low temperatures. The drying temperature of 50°C or below is not lethal to the microflora. The decimal reduction time (D-value) varied from 12.66 to 2.63 hr when drying temperature increased from 60 to 100°C, respectively. These values can be used to estimate the lethal effect of drying on the natural microflora in tuna.     

Characterization of endotoxic indicative organic matter (2-keto-3deoxyoctulosonic acid) in raw and biologically treated domestic wastewater

The aim of this research is to characterize the organic matter showing endotoxicity in domestic wastewater. It is assumed that endotoxicity is caused by lipo-polysaccharide (LPS), particularly large and hydrophobic molecules. In this study, a batch experiment (decay test for 12 h) was conducted to confirm whether LPS is the cause of endotoxicity or not. 2-keto-3deoxyoctulosonic acid (KDO) was used as an indicator of presence of LPS.A size and structural characterization of several samples from raw and domestic wastewater was also carried out in order know which fractions are causing endotoxicity. Endotoxin and KDO patterns were found to be similar, peaking at the same time. Thus, organic matter showing endotoxicity, such as LPS was released in the decay test. Moreover, the organic matter released from bacteria during decay test was partly biodegradable. Results from size characterization (Molecular Weight Distribution) showed that the majority of endotoxin (up to 82%), in domestic sewage and secondary effluents,is composed of molecules larger than 100 kDa and less than 0.1 μm. Similarly, structural characterization (hydrophobic and hydrophilic) showed that the majority of endotoxin, ranging from 59% to 83% of the total endotoxicity, is hydrophobic fractions. Therefore, removing large and hydrophobic molecules from wastewater can be an effective way to achieve a significant decrease in its endotoxicity.     

A robust and secure perceptual hashing system based on a quantization step analysis

Perceptual hashing is conventionally used for content identification and authentication. It has applications in database content search, watermarking and image retrieval. Most countermeasures proposed in the literature generally focus on the feature extraction stage to get robust features to authenticate the image, but few studies address the perceptual hashing security achieved by a cryptographic module. When a cryptographic module is employed [1], additional information must be sent to adjust the quantization step. In the perceptual hashing field, we believe that a perceptual hashing system must be robust, secure and generate a final perceptual hash of fixed length. This kind of system should send only the final perceptual hash to the receiver via a secure channel without sending any additional information that would increase the storage space cost and decrease the security. For all of these reasons, in this paper, we propose a theoretical analysis of full perceptual hashing systems that use a quantization module followed by a crypto-compression module. The proposed theoretical analysis is based on a study of the behavior of the extracted features in response to content-preserving/content-changing manipulations that are modeled by Gaussian noise. We then introduce a proposed perceptual hashing scheme based on this theoretical analysis. Finally, several experiments are conducted to validate our approach, by applying Gaussian noise, JPEG compression and low-pass filtering.     

Physicochemical properties of fermented Arabian mares' milk

Due to its numerous benefits, including health-promoting characteristics, there is increasing interest in finding product applications for mares' milk. In the present study, the physicochemical properties, turbidity and conductivity of Arabian mares' milk were studied during acidification by fermentation at 30 °C and compared with those of bovine milk. The data for the acidification rate were modelled using a logistic equation. Mares' milk showed a longer latency phase (284 min) and lower acidification rate (μ_max = 0.0052 dpH min^?1) compared with bovine milk (194 min and 0.0098 dpH min^?1 respectively). The general shape of the curves of the turbidity versus time and pH were similar in nature for the acidification of both milks. However, the characteristic points were different, due to the differences in casein micelle composition. Measurement of electrical conductivity during acidification showed that maximum demineralization of casein micelles started around pH 6.09 and 5.31, for mares' and bovine milk, respectively. In conclusion, the technological characteristics of mares' milk were very different from those of bovine milk, due to intrinsic physicochemical properties of both milks.     

Low‐complexity robust adaptive generalized sidelobe canceller detector for DS/CDMA systems

A novel low computational complexity robust adaptive blind multiuser detector, based on the minimum output energy (MOE) detector with multiple constraints and a quadratic inequality (QI) constraint is developed in this paper. Quadratic constraint has been a widespread approach to improve robustness against mismatch errors, uncertainties in estimating the data covariance matrix, and random perturbations in detector parameters. A diagonal loading technique is compulsory to achieve the quadratic constraint where the diagonal loading level is adjusted to satisfy the constrained value. Integrating the quadratic constraint into recursive algorithms seems to be a moot point since there is no closed‐form solution for the diagonal loading term. In this paper, the MOE detector of DS/CDMA system is implemented using a fast recursive steepest descent adaptive algorithm anchored in the generalized sidelobe canceller (GSC) structure with multiple constraints and a QI constraint on the adaptive portion of the GSC structure. The Lagrange multiplier method is exploited to solve the QI constraint. An optimal variable loading technique, which is capable of providing robustness against uncertainties and mismatch errors with low computational complexity is adopted. Simulations for several mismatch and random perturbations scenarios are conducted in a rich multipath environment with near–far effect to explore the robustness of the proposed detector. Copyright © 2008 John Wiley & Sons, Ltd.     

An investigation of cutting forces in machining with worn ball-end mill

Reliable tool wear monitoring technique is one of the important aspects for achieving an integrated and self-adjusting manufacturing system. In this study, an analytical model is proposed to estimate the cutting forces, the tool geometry, and the chip geometry in relation to the flank wear, when milling with a ball-end mill. Modeling is based on thermomechanical modelling of oblique cutting. The worn tool geometry is decomposed into a series of axial elementary cutting edges. At any active tooth element, the flank wear geometry is calculated and the chip formation is obtained from an oblique cutting process characterised by local undeformed chip section and local cutting angles. Coated carbide ball-end tool, and a titanium workpiece material have been considered in this paper. The results found by using developed models have shown good agreement with experimental results.     

Gas phase esterification of acetic acid with ethanol over MoO3 supported on AlPO4 and the effect of modification with phosphomolybdic acid and Ce4+ ions

A series of AIPO₄–MoO₃ (APM) systems with various molybdena loadings (5–50) mol %, same modified with phosphomolybdic acid (PMA) and cerium ions, were prepared by an impregnation method and calcined at 400 °C, except for the samples modified with PMA which were calcined at 350 °C for 4 h. The catalysts were characterized by TG/DTG, XRD, IR spectroscopy, N₂ adsorption and electrical conductivity measurements. The surface acidity and basicity of the catalysts were determined by adsorption of pyridine and the dehydration–dehydrogenation of isopropyl alcohol. The catalytic esterification of acetic acid with ethanol was carried out in a convention fixed bed reactor. The results clearly revealed that the catalyst with a composition of 10 mol % MoO₃ (APM10) was the most active and selective catalyst for the production of ethyl acetate. Moreover, the yield of ethyl acetate increases on addition of PMA into APM10 while it decreases on the addition of Ce⁴⁺ ions. These results were correlated with structure, semiconductivity and the acid–base properties of the prepared catalysts. Copyright © 2003 Society of Chemical Industry