Characterization of Fly Ash Sources in the Synthesis of Geopolymer

Silicon - Fly ash (FA) based geopolymers are affected by the reactive nature of FA, concentration and quantity of alkali activators and the curing conditions. However, for the geopolymer...     

Monitoring multivariate process variability when sub-group size is small

The current practice of multivariate process variability monitoring, when sub-group size is small, has nothing to do with probability of false alarm (PFA). Consequently, the reliability of the existing control charts remains undetermined. In this article, we propose a control chart which is reliable, very sensitive to the change in variance for small or moderate correlation, and provides a root causes analysis of an out-of-control signal. To illustrate these advantages, an industrial example is presented and the results are compared with those issued from the existing methods.     

Effect of chemical structure of aromatic dianhydrides on the thermal, mechanical and electrical properties of their terpolyimides with 4,4′-oxydianiline

Aromatic terpolyimides were synthesized by the reaction of 3,3′,4,4′-oxydiphthalicdianhydride(ODPA), 3,3′,4,4′-biphenyldianhydride(BPDA) and 3,3′,4,4′-benzophenonetetracaboxylicdianhydride(BTDA) with 4,4′-oxydianiline(ODA) via thermal imidization with the view to enhance their tensile properties without compromising thermal properties compared to their homo and copolyimides. Their films were characterized by FTIR, TGA, DSC and XRD. Their FTIR spectra established formation of polyimide by the characteristic vibrations at 1375cm⁻¹(C-N stretch) and 1113 cm⁻¹(imide ring deformation). TGA results showed imidization of residual polyamide acid close to 250 °C and decomposition of polyimides at about 540 °C. XRD results showed amorphous nature for all terpolyimides. Their tensile strength and tensile modulus were higher than either homo or copolyimides. Incorporation of BPDA, without bridging groups between the aromatic rings into the backbone of ODPA/BTDA-ODA is suggested as the cause for such an enhancement. Such terpolyimide can find application as adhesives in making flexible single/multilayer polyimide metal-clad laminates in flexible printed circuits and tape automated bonding applications. In addition, the terpolyimide, BPDA/BTDA/ODPA-ODA (mole ratio 0.5:0.25:0.25:1), showed low dielectric constant (3.52) as BPDA could offer slight rigidity by which the orientation of polar groupings could be reduced.     

Preparation and Characterization of N-Halamine-based Antimicrobial Fillers

The purpose of this study was to demonstrate that the surface of CaCO(3) fillers could be coated with an N-halamine based fatty acid to make the filler surface organophilic and accomplish antibacterial activity simultaneously, rendering the resulting polymer-filler composites antimicrobial. Thus, a new bi-functional compound, 4, 4 -Dimethyl hydantoin-undecanoic acid (DMH-UA), was synthesized by treating the potassium salt of dimethyl hydantoin (DMH) with 11-bromoundecanoic acid (BUA). Upon chlorination treatment with diluted bleach, DMH-UA was transformed into 3-chloro-4, 4-dimethyl hydantoin- undecanoic acid (Cl-DMH-UA). Alternatively, DMH-UA could be coated onto the surface of CaCO(3) to obtain the corresponding calcium salt, 4, 4-dimethyl hydantoin-undecanoic acid-calcium carbonate (DMH-UA-CaCO(3)). In the presence of diluted chlorine bleach, the coated DMH-UA on the surface of CaCO(3) was transformed into Cl-DMH-UA, leading to the formation of Cl-DMH-UA-CaCO(3). The reactions were characterized with FT-IR, NMR, UV, DSC and SEM analyses. Both Cl-DMH-UA and Cl-DMH-UA-CaCO(3) were used as antimicrobial additives for cellulose acetate (CA). The antimicrobial efficacy of the resulting samples was evaluated against both Escherichia coli (Gram-negative bacteria) and Staphylococcus aureus (Gram-positive bacteria). It was found that with the same additive content, CA samples with Cl-DMH-UA-CaCO(3) and Cl-DMH-UA had very similar antimicrobial and biofilm-controlling activity, but the former released less active chlorine into the surrounding environment than the latter.     

Palladium‐nanoparticle intercalated vermiculite for selective hydrogenation of α,β‐unsaturated aldehydes

Palladium nanoparticles were generated in the interlamellar region of swelling 2:1 type vermiculite clay using an adsorption excess isotherm. An adsorption excess isotherm was constructed for vermiculite after exchanging the exchangeable Na⁺ ions in the interlamellar region using a binary liquid mixture (ethanol:toluene). Based on adsorption excess isotherm, 1% w/w palladium was intercalated into the interlamellar space of vermiculite. The Pd‐intercalated vermiculite was characterized by X‐ray diffraction, transmission electron microscopy and atomic absorption spectroscopy. The 1% w/w Pd‐intercalated vermiculite was tested for its catalytic activity towards selective hydrogenation reactions involving some α,β‐unsaturated carbonyl compounds using a pulse reactor and its catalytic activity was compared with commercial 1% Pd/C. The intercalated catalyst was found to be very selective towards the desired product of unsaturated alcohols. Copyright © 2007 Society of Chemical Industry     

Role of Mn impurity in the deterioration of ZnS:Cu,Br electroluminescent phosphors

ZnS:Cu, Br powder EL phosphors showed 6-line EPR signal at 25°C whose intensity increases with Cu content and on annealing in Zn-vapour. The signal arises from native Mn impurity. The starting material does not show any EPR signal since Mn²⁺ acts as an affinity potential well for a hole in ZnS, forming Mn³⁺ - a chemically uncommon situation in sulfides. In doped ZnS, holes are trapped at Cu such that Mn²⁺ persists. Deterioration of EL brightness is accompanied by the decrease in EPR signal intensity due to field assisted hole transference to Mn²⁺. Intentional addition of Mn in ZnS:Cu, Br decreases the brightness and shortens life time. Stable phosphors require ZnS with Mn content less than 10¹⁴ cm^?3.     

Nature inspired discrete firefly algorithm for optimal mobile data gathering in wireless sensor networks

Nowadays wireless sensor networks enhance the life of human beings by helping them through several applications like precision agriculture, health monitoring, landslide detection, pollution control, etc. The built-in sensors on a sensor node are used to measure the various events like temperature, vibration, gas emission, etc., in the remotely deployed unmanned environment. The limited energy constraint of the sensor node causes a huge impact on the lifetime of the deployed network. The data transmitted by each sensor node cause significant energy consumption and it has to be efficiently used to improve the lifetime of the network. The energy consumption can be reduced significantly by incorporating mobility on a sink node. Thus the mobile data gathering can result in reduced energy consumption among all sensor nodes while transmitting their data. A special mobile sink node named as the mobile data transporter (MDT) is introduced in this paper to collect the information from the sensor nodes by visiting each of them and finally it sends them to the base station. The Data collection by the MDT is formulated as a discrete optimization problem which is termed as a data gathering tour problem. To reduce the distance traveled by the MDT during its tour, a nature-inspired heuristic discrete firefly algorithm is proposed in this paper to optimally collect the data from the sensor nodes. The proposed algorithm computes an optimal order to visit the sensor nodes by the MDT to collect their data with minimal travel distance. The proposed algorithm is compared with tree-based data collection approaches and ant colony optimization approach. The results demonstrate that the proposed algorithm outperform other approaches minimizing the tour length under different scenarios.     

An efficient system for anomaly detection using deep learning classifier

In this paper, a deep learning-based anomaly detection (DLAD) system is proposed to improve the recognition problem in video processing. Our system achieves complete detection of abnormal events by involving the following significant proposed modules a Background Estimation (BE) Module, an Object Segmentation (OS) Module, a Feature Extraction (FE) Module, and an Activity Recognition (AR) Module. At first, we have presented a BE (Background Estimation) module that generated an accurate background in which two-phase model is generated to compute the background estimation. After a high-quality background is generated, the OS model is developed to extract the object from videos, and then, object tracking process is used to track the object through the overlapping detection scheme. From the tracked objects, the FE module is extracted for some useful features such as shape, wavelet, and histogram to the abnormal event detection. For the final step, the proposed AR module is classified as abnormal or normal event using the deep learning classifier. Experiments are performed on the USCD benchmark dataset of abnormal activities, and comparisons with the state-of-the-art methods validate the advantages of our algorithm. We can see that the proposed activity recognition system has outperformed by achieving better EER of 0.75 % when compared with the existing systems (20 %). Also, it shows that the proposed method achieves 85 % precision rate in the frame-level performance.     

Hybrid Authentication Using Node Trustworthy to Detect Vulnerable Nodes

An ad-hoc sensor network (ASN) is a group of sensing nodes that transmit data over a wireless link to a target node, direct or indirect, through a series of nodes. ASN becomes a high-risk group for several security exploits due to the sensor node’s limited resources. Internal threats are more challenging to protect against than external attacks. The nodes are grouped, and calculate each node’s trust level. The trust level is the result of combining internal and external trust degrees. Cluster heads (CH) are chosen based on the anticipated trust levels. The communications are then digitally signed by the source, encoded using a key pair given by a trustworthy CH, decoded by the recipient, and supervised by verifications. It authenticates the technique by identifying the presence of both the transmitter and the recipient. Our approach looks for a trustworthy neighboring node that meets the trust threshold condition to authenticate the key produced. The companion node reaffirms the node’s reliability by getting the public-key certification. The seeking sensor node and the certification issuer node must have a close and trusting relationship. The results of the proposed hybrid authentication using a node trustworthy (HANT) system are modeled and tested, and the suggested approach outperforms conventional trust-based approaches in throughput, latency, lifetime, and vulnerability methods.     

Multistep temperature prediction for proactive thermal management on chip multiprocessors

The Journal of Supercomputing - In chip multiprocessors, the thermal hot spot prediction is vital to take proactive thermal management decisions for mitigating its impact on the performance of the...