Bayesian inference for partially accelerated life tests using Gibbs sampling

We consider a life testing situation in which several groups of items are put, at different instances, on the partially accelerated life test proposed by DeGroot and Goel [Naval Research Logistics Quarterly, 1979. 26, 223–235]. The combined failure time data are then used to derive empirical Bayes estimators for the failure of the exponential life length under normal conditions. The estimation which is implemented using the Gibbs sampler Monte-Carlo-based approach, illustrates once again the ease with which these new types of estimation problems often requiring sophisticated numerical or analytical expertise, can be handled using the sampling based approach.     

Hybrid method combining superpixel,supervised learning,and random walk for glioma segmentation

Currently, the analysis of magnetic resonance imaging (MRI) brain images of pathological patients is performed manually, both for the recognition of brain structures or lesions and for their characterization. Physicians sometimes encounter difficulties in interpreting these images for a reliable diagnosis of the patient's condition. This is due to the difficulty of detecting the nature of the lesions, particularly glioma. Glioma is one of the most common tumors, and one of the most difficult to detect because of its shape, irregularities, and ambiguous limits. The segmentation of these tumors is one of the most crucial steps for their classification and surgical planning. This article presents a new, accurate, and automatic approach for the precise segmentation of early gliomas (benign tumors), combining the random walk (RW) algorithm and the simple linear iterative clustering algorithm. The study was carried out in four steps. The first step consisted of decomposing the image into superpixels to obtain an initial outline of the tumor. The superpixels were generated using the SLIC algorithm. In the second step, for each superpixel, a set of statistical and multifractal characteristics were calculated (gray‐level co‐occurrence matrix, multifractal detrending moving average). In the third step, the superpixels were classified using a supervised random forest (RF) type classier into healthy or tumorous brain tissue. In the final step, the contour of the detected tumor was enhanced using the customized RW algorithm. The proposed method was evaluated using the Brain Tumor Image Segmentation Challenge 2013 database. The results obtained are competitive compared to other existing methods.     

Traffic Priority-Aware Medical Data Dissemination Scheme for IoT Based WBASN Healthcare Applications

Wireless Body Area Sensor Network (WBASN) is an automated system for remote health monitoring of patients. WBASN under umbrella of Internet of Things (IoT) is comprised of small Biomedical Sensor Nodes (BSNs) that can communicate with each other without human involvement. These BSNs can be placed on human body or inside the skin of the patients to regularly monitor their vital signs. The BSNs generate critical data as it is related to patient's health. The data traffic can be classified as Sensitive Data (SD) and Non-sensitive Data (ND) packets based on the value of vital signs. These data packets have different priority to deliver. The ND packets may tolerate some delay or packet loss whereas, the SD packets required to be delivered on time with minimized packet loss otherwise it can be life threating to the patients. In this research, we propose a Traffic Priority-aware Medical Data Dissemination (TPMD²) scheme for WBASN to deliver the data packets according to their priority based on the sensitivity of the data. The assessment of the proposed scheme is carried out in various experiments. The simulation results of the TPMD² scheme indicate a significant improvement in packets delivery, transmission delay and energy efficiency in comparison with the existing schemes.     

PLR-based heuristic for backup path computation in MPLS networks

To ensure service continuity in networks, local protection pre-configuring the backup paths is preferred to global protection. Under the practical hypothesis of single physical failures in the network, the backup paths which protect against different logical failure risks (node, link and shared risk link group (SRLG)) cannot be active at the same time. Thus, sharing bandwidth between such backup paths is crucial to increase the bandwidth availability.In this article, we focus on the optimal on-line distributed computation of the bandwidth-guaranteed backup paths in MPLS networks. As the requests for connection establishment and release arrive dynamically without knowledge of future arrivals, we choose to use the on-line mode to avoid LSP reconfigurations. We also selected a distributed computation to offer scalability and decrease the LSP setup time. Finally, the optimization of bandwidth utilization can be achieved thanks to the flexibility of the path choice offered by MPLS and to the bandwidth sharing.For a good bandwidth sharing, the backup path computation entities (BPCEs) require the knowledge and maintenance of a great quantity of bandwidth information (e.g. non aggregated link information or per path information) which is undesirable in distributed environments. To get around this problem, we propose here a PLR (point of local repair)-based heuristic (PLRH) which aggregates and noticeably decreases the size of the bandwidth information advertised in the network while offering a high bandwidth sharing. PLRH permits an efficient computation of backup paths. It is scalable, easy to be deployed and balances equitably computations on the network nodes.Simulations show that with the transmission of a small quantity of aggregated information per link, the ratio of rejected backup paths is low and close to the optimum.     

Electrical and thermal properties of highly quenched amorphous V2O5 thin films

Amorphous thin films of V₂O₅ have been prepared by vapour deposition in high vacuum ( 10^–6 torr). In order to study the role of quenching, various temperatures, ranging from –196 to 260° C, have been selected for the substrate. Differential thermal analysis. X-ray diffraction and conductivity measurements clearly divide the material into two sets, depending on the efficiency of the quenching. Whereas the least-quenched samples resemble those previously obtained by splat-cooling, the better quenched are only barely stable and, as a consequence, exhibit unique features, such as the occurrence of a glassy transition and the highest crystallization temperature ever found for V₂O₅.     

Evaluation using online support-vector-machines and fuzzy reasoning. Application to condition monitoring of speeds rolling process

A method for process condition monitoring and evaluation, which combines the online support vector machine (SVM) regression and the fuzzy sets methods, is proposed. To account for the time dependence, the proposed approach is based on moving windows in order to take into account the past and new data for the model’s adaptation. The fuzzy analysis is then applied to the generated residual data to give an evaluation of the condition monitoring. The proposed approach is applied to hot rolling for constructing a complementary condition monitoring system, which permits an online quality evaluation in the rolling process. Simulation results based on residual data show that the new approach is easily implementable.     

In situ and real-time 3-D microtomography investigation of dendritic solidification in an Al–10 wt.% Cu alloy

The microstructural evolution of an Al–10 wt.% Cu alloy was investigated during solidification at constant cooling rate by in situ synchrotron X-ray microtomography with a resolution of 2.8 μm. Solidification of this alloy leads to a coarse dendritic microstructure which was fully characterized in terms of variation with temperature of the solid fraction, the specific surface area of the solid–liquid interface and the local curvatures of the solid phase. By analysing the evolution with solid fraction of individual dendrites, at least two coarsening mechanisms were clearly identified in addition to solidification growth. The first mechanism involves remelting of small secondary dendrite arms to the benefit of bigger adjacent arms. The second is the coalescence of adjacent secondary arms, with progressive filling of the inter-arm spacing and coalescence at the tips. Although this mechanism preferentially occurs at high solid fractions, these results show that the evolution of the dendritic microstructure during solidification is complex and involves the occurrence of various mechanisms operating concurrently. In situ X-ray tomography thus allows revisiting the various models which have been proposed to account for dendrite coarsening during solidification.     

Mechanical Characterization of Basalt/HDPE Composite under In-Vitro Condition

The objective of this study was to characterize the mechanical behaviour of basalt/HDPE composite under in-vitro condition. Basalt fiber has been performed as an alternative reinforcement material to reduce the domination of the synthetic fibers such as carbon and E-glass fiber in the medical application. Mechanical testing such as tensile, flexural and impact were performed to determine this composite performance before in-vitro testing conducted. Comparisons have been done towards carbon and E-glass using HDPE as a resin. In-vitro testing of basalt/HDPE was conducted in duration 4 weeks. The results shows the basalt/HDPE has a higher mechanical properties compared to E-glass/HDPE and lower compared to carbon/HDPE. Results of tensile and flexural after in-vitro testing are slightly reduced in 5% by week. Charpy impact test of Basalt/HDPE was performed and also experience a reduction in 7% of strength value. Scanning Electron Microscope (SEM) is used to analyze the surface and texture morphology before and after in-vitro testing. No bio-activity or significant changes have been identified at the Basalt/HDPE composite based on the SEM data. It can be concluded that the basalt/HDPE was combined well as a composite material under in-vitro condition as well can be introduce in medical application.     

Enantiomeric and non-enantiomeric monoterpenes of Juniperus communis L. and Juniperus oxycedrus needles and berries determined by HS-SPME and enantioselective GC/MS

For the first time, enantiomeric and non-enantiomeric distribution of monoterpenes in the headspace of Juniperus communis L. and Juniperus oxycedrus needles and berries has been determined using HS-SPME combined with enantioselective GC/MS. The essential oils from needles and berries of both Juniperus species obtained by hydrodistillation were also performed. HS-SPME has shown good potential to reproduce the same results as the commonly used hydrodistillation extraction technique. While needles and berries of J. communis showed high contents of sabinene, α-pinene and β-myrcene with 19-30%, 12-24% and 9-20%, respectively, J. oxycedrus was strongly dominated by α-pinene with 85-92% in both needles and berries. Large variations in chiral distribution of monoterpenes within the same plant species and between the two junipers were observed. Interestingly, similar enantiomeric preferences of monoterpenes were obtained between needles and berries of the two junipers.