Using Shared Risk Link Groups to enhance backup path computation

To cope quickly with all types of failure risks (link, node and Shared Risk Link Group (SRLG)), each router detecting a failure on an outgoing interface activates locally all the backup paths protecting the primary paths which traverse the failed interface. With the observation that upon a SRLG failure, some active backup paths are inoperative and do not really participate to the recovery (since they do not receive any traffic flow), we propose a new algorithm (SRLG structure exploitation algorithm or SSEA) exploiting the SRLG structures to enhance the admission control and improve the protection rate.With our algorithm, more flexibility is provided for the backup path selection since a backup path which protects against the failure of a link belonging to a SRLG does not systematically bypass all the links of that SRLG. Moreover, our algorithm permits to save more bandwidth because it does not allocate the bandwidth for the inoperative backup paths even if they are activated.Simulations show that our algorithm SSEA decreases the ratio of rejected backup paths and, it reduces in distributed environments the average number of messages sent to manage the bandwidth information necessary for the backup path computation.     

Multiatlas‐based segmentation of female pelvic organs: Application for computer‐aided diagnosis of cervical cancer

Atlas‐based segmentation is a high level segmentation technique which has become a standard paradigm for exploiting prior knowledge in image segmentation. Recent multiatlas‐based methods have provided greatly accurate segmentations of different parts of the human body by propagating manual delineations from multiple atlases in a data set to a query subject and fusing them. The female pelvic region is known to be of high variability which makes the segmentation task difficult. We propose, here, an approach for the segmentation of magnetic resonance imaging (MRI) called multiatlas‐based segmentation using online machine learning (OML). The proposed approach allows separating regions which may be affected by cervical cancer in a female pelvic MRI. The suggested approach is based on an online learning method for the construction of the dataset of atlases. The experiments demonstrate the higher accuracy of the suggested approach compared to a segmentation technique based on a fixed dataset of atlases and single‐atlas‐based segmentation technique.     

Optimization of Serine Protease Purification from Mango (Mangifera indica cv. Chokanan) Peel in Polyethylene Glycol/Dextran Aqueous Two Phase System

Mango peel is a good source of protease but remains an industrial waste. This study focuses on the optimization of polyethylene glycol (PEG)/dextran-based aqueous two-phase system (ATPS) to purify serine protease from mango peel. The activity of serine protease in different phase systems was studied and then the possible relationship between the purification variables, namely polyethylene glycol molecular weight (PEG, 4000-12,000 g·mol(-1)), tie line length (-3.42-35.27%), NaCl (-2.5-11.5%) and pH (4.5-10.5) on the enzymatic properties of purified enzyme was investigated. The most significant effect of PEG was on the efficiency of serine protease purification. Also, there was a significant increase in the partition coefficient with the addition of 4.5% of NaCl to the system. This could be due to the high hydrophobicity of serine protease compared to protein contaminates. The optimum conditions to achieve high partition coefficient (84.2) purification factor (14.37) and yield (97.3%) of serine protease were obtained in the presence of 8000 g·mol(-1) of PEG, 17.2% of tie line length and 4.5% of NaCl at pH 7.5. The enzymatic properties of purified serine protease using PEG/dextran ATPS showed that the enzyme could be purified at a high purification factor and yield with easy scale-up and fast processing.     

Online in situ x-ray diffraction setup for structural modification studies during swift heavy ion irradiation

The high energy density of electronic excitations due to the impact of swift heavy ions can induce structural modifications in materials. We present an x-ray diffractometer called ALIX ("Analyse en Ligne sur IRRSUD par diffraction de rayons X"), which has been set up at the low-energy beamline (IRRadiation SUD - IRRSUD) of the Grand Acce?le?rateur National d'Ions Lourds facility, to allow the study of structural modification kinetics as a function of the ion fluence. The x-ray setup has been modified and optimized to enable irradiation by swift heavy ions simultaneously to x-ray pattern recording. We present the capability of ALIX to perform simultaneous irradiation-diffraction by using energy discrimination between x-rays from diffraction and from ion-target interaction. To illustrate its potential, results of sequential or simultaneous irradiation-diffraction are presented in this article to show radiation effects on the structural properties of ceramics. Phase transition kinetics have been studied during xenon ion irradiation of polycrystalline MgO and SrTiO(3). We have observed that MgO oxide is radiation-resistant to high electronic excitations, contrary to the high sensitivity of SrTiO(3), which exhibits transition from the crystalline to the amorphous state during irradiation. By interpreting the amorphization kinetics of SrTiO(3), defect overlapping models are discussed as well as latent track characteristics. Together with a transmission electron microscopy study, we conclude that a single impact model describes the phase transition mechanism.     

Characterization of Headspace Volatile Flavor Compounds Formed During Kefir Production: APplication of Solid Phase MicroextractioN

Headspace volatile flavor compounds of kefir were monitored using headspace solid phase microextraction (HS-SPME) method during fermentation of milk with kefir starter culture. Among all flavor compounds, forty volatile compounds were initially detected using gas chromatography coupled to time-of-flight mass spectrometer (GC-TOFMS). Consequently, eight volatile flavor compounds, namely ethanol, ethyl acetate, ethyl butyrate, 2-butanone, acetone, 3-hydroxy-2-butanone (acetoin), 2,3-butanedione (diacetyl) and acetaldehyde were considered as the representative of the alcohol, ketone, ester and aldehyde compounds in kefir. Moreover, in term of quantitative analysis, more than 97% of total flavor compounds composed of the proposed volatile flavor compounds. The results indicated that the concentration of 2-butanone released into headspace of kefir was found to be stable during fermentation. The release content of other volatile flavor compounds increased throughout the fermentation process. However, the headspace concentration of acetoin significantly (P < 0.05) decreased between pH 5.2 and 4.6.     

Electrolytic treatment of Standard Malaysian Rubber process wastewater

A new method of Standard Malaysian Rubber (SMR) process wastewater treatment was developed based on in situ hypochlorous acid generation. The hypochlorous acid was generated in an undivided electrolytic cell consisting of two sets of graphite as anode and stainless sheets as cathode. The generated hypochlorous acid served as an oxidizing agent to destroy the organic matter present in the SMR wastewater. For an influent COD concentration of 2960 mg/L at an initial pH 4.5+/-0.1, current density 74.5 mA/cm(2), sodium chloride content 3% and electrolysis period of 75 min, resulted in the following residual values pH 7.5, COD 87 mg/L, BOD(5) 60 mg/L, TOC 65 mg/L, total chlorine 146 mg/L, turbidity 7 NTU and temperature 48 degrees C, respectively. In the case of 2% sodium chloride as an electrolyte for the above said operating condition resulted in the following values namely: pH 7.2, COD 165 mg/L, BOD(5) 105 mg/L, TOC 120 mg/L, total chlorine 120 mg/L, turbidity 27 NTU and temperature 53 degrees C, respectively. The energy requirement were found to be 30 and 46 Wh/L, while treating 24 L of SMR wastewater at 2 and 3% sodium chloride concentration at a current density 74.5 mA/cm(2). The observed energy difference was due to the improved conductivity at high sodium chloride content.     

Detection of Electrical Fault in Medium Voltage Installation Using Support Vector Machine and Artificial Neural Network

Russian Journal of Nondestructive Testing - Infrared thermography plays an important role in the inspection of electrical installations allowing to avoid failures and breakdowns. Condition...     

Exudates segmentation using inverse surface adaptive thresholding

This paper presents a new approach to detect exudates and optic disc from color fundus images based on inverse surface thresholding. The strategy involves the applications of fuzzy c-means clustering, edge detection, otsu thresholding and inverse surface thresholding. The main advantage of the proposed approach is that it does not depend on manually selected parameters that are normally chosen to suit the tested databases. When applied to two sets of databases the proposed method outperforms methods based on watershed segmentation and morphological reconstruction. The proposed method obtained 98.2 and 90.4 in terms of sensitivity for Standard Diabetic Retinopathy Database – Calibration Level 1 (DIARETDB1) and a local dataset provided by National University Hospital of Malaysia (NUHM), respectively.     

Congestion control methods for BISDN

Several congestion control methods for asynchronous transfer mode (ATM,) networks that support multimedia traffic by providing different guaranteed quality for each class of traffic are discussed. The two categories of congestion control methods presented are preventive congestive control and reactive congestive control. Preventive congestion control takes any action necessary to prevent congestion Reactive congestion control is responsible for any necessary action to recover from a congested situation, A summary of a proposed multilevel control scheme is also presented     

Inferential sensor – Based adaptive principal components analysis for mechanical properties prediction and evaluation

This paper is concerned with a method for on-line quality prediction and evaluation of mechanical properties in metal testing. This method uses an Adaptive Principal Component Analysis (APCA) as a multi predictor of different sub-models defining the mechanical properties such as constraints limits and elongation. The PCA technique, characterized by its multivariate component, is strongly recommended to model a multi-input-multi-output system. The complex system is generally known as a non-linear and unsteady state process. The PCA method is a linear projection. To adapt it and to improve the prediction accuracy, a variant of this method is considered based on iteratively using a specific algorithm. This kind of approaches is applied for constructing an inferential model, which allows a reliable and accurate predictor. Simulation results, based on the measured and computed data using the above-cited method, show that the proposed approach is easily implementable and give an accurate prediction.