Novel catechol-derived phosphorus-based precursors for coating applications

Polymer Bulletin - Depletion of the petroleum resources and poor flame-retardant properties of the epoxy resins drive researchers to develop an epoxy resin with good heat stability from...     

Engineering plastics from lignin. VI. Structure–property relationships of PEG-containing polyurethane networks

Hydroxypropyl lignin-based thermosetting polyurethanes were synthesized with excess hexamethylene diisocyanate (HDI) and tolylene diisocyanate (TDI) by solution casting. Four polyethylene glycols (PEG) of molecular weight 400, 600, 1000, and 4000 were mixed with lignin polyol to incorporate different proportions of soft segment into the network prior to crosslinking. Neither thermal nor mechanical and limited small angle x-ray scattering (SAXS) analysis provided distinct evidence for phase separation and microstructure formation. The study examines the effect of the soft segment in relation to chain length and weight contribution on the thermal and mechanical properties of the final networks. A significant sensitivity of glass transition temperature (T_g), of swelling in DMF, and of the mechanical properties to soft segment content was observed. Some of this sensitivity must, however, be attributed to differences in crosslink density since the polyol to diisocyanate weight ratio was kept constant throughout the synthesis series. The magnitude of the change of the different properties was found to be influenced by both glycol content and glycol molecular weight. The T_g of the network decreased from 105°C to as low as 38°C (HDI), and from 158°C to 70°C (TDI), with incorporation of up to 17.8% glycol, and it was greater with lower molecular weight glycols than with higher ones at any weight fraction. Swelling in DMF increased as expected with soft segment content. Mechanical properties were affected most if HDI and lower molecular weight glycols were used. The uniformity in structure, reduction in brittleness, and considerable improvement in mechanical properties with inclusion of minor PEG contents indicates that lignin-based network polyurethanes can be synthesized with controllable performance characteristics.     

How does organisational absorptive capacity matter in the assimilation of enterprise information systems?

Extant literature offers two mostly distinct perspectives on enterprise systems assimilation – driven either by internal expertise and learning capability or by external institutional pressures. This study combines the two perspectives and subscribes to the view that organisations’ learning capability moderates their acquiescence to institutional pressures. The study then anchors organisational learning capability to the concept of absorptive capacity and proposes that its two dimensions – potential absorptive capacity (PACAP) and realised absorptive capacity (RACAP) – affect enterprise systems assimilation through different pathways. Our survey‐based empirical study of Enterprise Resource Planning (ERP) systems in the post‐implementation stage reveals that while both PACAP and RACAP have a positive direct impact on assimilation, PACAP positively moderates the impact of mimetic (institutional) pressures, but not normative (institutional) pressures, on assimilation; whereas RACAP positively moderates the impact of normative pressures, but not mimetic pressures, on assimilation. Thus, our theoretical contribution lies in understanding the distinct ways in which PACAP and RACAP moderate the influence of external institutional pressures on enterprise systems assimilation.     

Manifold Preserving Features and Regression for Semantic Labelling in High Dimensional Images

Wireless Personal Communications - This paper proposes an combined method for manifold preservation and Subspace Eigenvectors(SE) based regression in high dimensional (HD) images. We studied...     

Magnetic field-assisted photochemical machining (MFAPCM) of SS316L

In this paper, a new technique of photochemical machining (PCM) process has been described. The objective of this study is to investigate the effect of applying a magnetic field on the PCM of AISI 316?L stainless steel. The experiments were planned and conducted using a Full Factorial Design (FFD) approach. The control parameters selected were magnetic field, temperature, concentration and time. The analysis of the results shows significant improvement in the etch rate due to the application of a magnetic field. The highest etch rate was achieved at a concentration of 700?g/l, at the temperature of 60°C in a static magnetic field. The improvement of the etch rate is 2.5 times with the application of magnetic field as compared to the conventional PCM process.     

Thermodynamic properties and phase equilibria for Pt-Rh alloys

The activity of rhodium in solid Pt-Rh alloys is measured in the temperature range from 900 to 1300 K using the solid-state cell

Integrated Data Management for a Fleet of Search‐and‐rescue Robots

Search‐and‐rescue operations have recently been confronted with the introduction of robotic tools that assist the human search‐and‐rescue workers in their dangerous but life‐saving job of searching for human survivors after major catastrophes. However, the world of search and rescue is highly reliant on strict procedures for the transfer of messages, alarms, data, and command and control over the deployed assets. The introduction of robotic tools into this world causes an important structural change in this procedural toolchain. Moreover, the introduction of search‐and‐rescue robots acting as data gatherers could potentially lead to an information overload toward the human search‐and‐rescue workers, if the data acquired by these robotic tools are not managed in an intelligent way. With that in mind, we present in this paper an integrated data combination and data management architecture that is able to accommodate real‐time data gathered by a fleet of robotic vehicles on a crisis site, and we present and publish these data in a way that is easy to understand by end‐users. In the scope of this paper, a fleet of unmanned ground and aerial search‐and‐rescue vehicles is considered, developed within the scope of the European ICARUS project. As a first step toward the integrated data‐management methodology, the different robotic systems require an interoperable framework in order to pass data from one to another and toward the unified command and control station. As a second step, a data fusion methodology will be presented, combining the data acquired by the different heterogenic robotic systems. The computation needed for this process is done in a novel mobile data center and then (as a third step) published in a software as a service (SaaS) model. The SaaS model helps in providing access to robotic data over ubiquitous Ethernet connections. As a final step, we show how the presented data‐management architecture allows for reusing recorded exercises with real robots and rescue teams for training purposes and teaching search‐and‐rescue personnel how to handle the different robotic tools. The system was validated in two experiments. First, in the controlled environment of a military testing base, a fleet of unmanned ground and aerial vehicles was deployed in an earthquake‐response scenario. The data gathered by the different interoperable robotic systems were combined by a novel mobile data center and presented to the end‐user public. Second, an unmanned aerial system was deployed on an actual mission with an international relief team to help with the relief operations after major flooding in Bosnia in the spring of 2014. Due to the nature of the event (floods), no ground vehicles were deployed here, but all data acquired by the aerial system (mainly three‐dimensional maps) were stored in the ICARUS data center, where they were securely published for authorized personnel all over the world. This mission (which is, to our knowledge, the first recorded deployment of an unmanned aerial system by an official governmental international search‐and‐rescue team in another country) proved also the concept of the procedural integration of the ICARUS data management system into the existing procedural toolchain of the search and rescue workers, and this in an international context (deployment from Belgium to Bosnia). The feedback received from the search‐and‐rescue personnel on both validation exercises was highly positive, proving that the ICARUS data management system can efficiently increase the situational awareness of the search‐and‐rescue personnel.     

Classifying the Geometric Dilution of Precision of GPS satellites utilizing Bayesian decision theory

The errors resulting from satellite configuration geometry can be determined by Geometric Dilution of Precision (GDOP). Considering optimal satellite subset selection, lower GDOP value usually causes better accuracy in GPS positioning. However, GDOP computation based on complicated transformation and inversion of measurement matrices is a time consuming procedure. This paper deals with classification of GPS GDOP utilizing Parzen estimation based Bayesian decision theory. The conditional probability of each class is estimated by Parzen algorithm. Then based on Bayesian decision theory, the class with maximum posterior probability is selected. The experiments on measured dataset demonstrate that the proposed algorithm lead, in mean classification improvement, to 4.08% in comparison with Support Vector Machine (SVM) and 9.83% in comparison with K-Nearest Neighbour (KNN) classifier. Extra work on feature extraction has been performed based on Principle Component Analysis (PCA). The results demonstrate that the feature extraction approach has best performance respect to all classifiers.