High performance multi-layer varistor (MLV) from doped ZnO nanopowders by water based tape casting: Rheology,sintering, microstructure and properties

In this work, we report the fabrication of a high performance multi-layer varistor (MLV) via water based tape casting method using novel compositions of nanomaterials. Bi₂O₃, CaO and Co₃O₄ doped ZnO nanopowders were prepared by solution combustion synthesis (SCS) route, calcined at different temperatures (550, 650, 750 and 850?°C) and characterized by TEM, XRD, SEM and AFM. The nanopowder (crystallite size ~30?nm) calcined at 650?°C for 1?h was used as the starting material for MLV fabrication. Compositions of the slurry containing doped ZnO nanopowders, binder and plasticizer in water solvent were optimized for the fabrication of thick film. The rheological properties of the slurries having different solid loadings were analysed and thick films of various thicknesses (50–500?µm) were prepared by varying the feeding rate of tape casting. The film roughness of 38.3?nm for the thick film made from 40?wt% solid slurry was found to be superior compared to other samples due to the presence of reduced crack and shrinkage. MLV fired at 950?°C for 1.5?h exhibited a coefficient of nonlinearity of 18 and breakdown voltage of 291.5?V that yields superior properties compared to commercial MLVs.     

Calf massager: Intervention for body muscle discomfort during prolonged standing

Many occupations require workers to stand for long periods of time without proper interventions, which causes discomfort in the back and lower limbs. Therefore, this study aims to assess the effectiveness in alleviating body muscle discomfort during prolonged standing through the use of a calf massager. This study was conducted among male workers at a manufacturer with production line workers and the list was obtained from the HR Department and simple random sampling was done by number categorization. A total of 100 respondents (50 respondents for both the control and the experimental groups) participated in this study. The experiment took place in a room with a similar setup for the production line. Each respondent was requested to perform the simulated task for 2 hr. For the experimental group, the calf massager was turned on every 15 min. At every 15‐min interval after turning on the calf massager, respondents from both groups were required to evaluate their discomfort level on a Borg's scale CR‐10 questionnaire. The results showed that the level of body discomfort among respondents in the experimental group reduced (20–30%) compared with that of the control group. Multivariate analysis results revealed that the discomfort rating for the lower back, knees, thighs, calves, and feet was significantly lower (p < .05) among the experimental group compared with the control group. For lower body parts, the lower back region was statistically significant (p < .05) at the 90th, 105th, and 120th min; the thigh region was statistically significant (p < .05) at the 120th min; the knee region was statistically significant (p < .05) at the 105th and 120th min; the calf region was statistically significant (p < .05) at all minute intervals except the 15th and 45th min, while the feet region, was statistically significant at the 105th and 120th min. Therefore, this study indicates that calf massage treatment is capable of reducing body muscle discomfort during prolonged standing and highlights the significance of calf massage.     

Machine learning techniques for anti-money laundering (AML) solutions in suspicious transaction detection: a review

Money laundering has been affecting the global economy for many years. Large sums of money are laundered every year, posing a threat to the global economy and its security. Money laundering encompasses illegal activities that are used to make illegally acquired funds appear legal and legitimate. This paper aims to provide a comprehensive survey of machine learning algorithms and methods applied to detect suspicious transactions. In particular, solutions of anti-money laundering typologies, link analysis, behavioural modelling, risk scoring, anomaly detection, and geographic capability have been identified and analysed. Key steps of data preparation, data transformation, and data analytics techniques have been discussed; existing machine learning algorithms and methods described in the literature have been categorised, summarised, and compared. Finally, what techniques were lacking or under-addressed in the existing research has been elaborated with the purpose of pinpointing future research directions.     

Catalytic packed bed non‐thermal plasma reactor for the extraction of hydrogen from hydrogen sulfide

The decomposition of hydrogen sulfide (H₂S) to hydrogen and sulfur with Al₂O₃, MoO_x/Al₂O₃, CoO_x/Al₂O₃ and NiO/Al₂O₃ packed non‐thermal plasma dielectric barrier discharge reactor was studied. The reaction was carried out with 5‐mm discharge gap during the decomposition of 5 vol.% H₂S at 150 ml/min (STP) flow rate. Typical results indicated the conversion of ~50% at a specific input energy of ~0.92 kJ/l H₂S and 10% (in length) packed reactor showed the best conversion. Among the catalysts studied, MoO_x and CoO_x supported on Al₂O₃ showed high performance, which may be caused by synergy between plasma excitation of the carrier gas molecules and catalytic behaviour of MoO_x and CoO_x. Copyright © 2012 John Wiley & Sons, Ltd.     

Optimal Feature Extraction Using Greedy Approach for Random Image Components and Subspace Approach in Face Recognition

An innovative and uniform framework based on a combination of Gabor wavelets with principal component analysis (PCA) and multiple discriminant analysis (MDA) is presented in this paper. In this framework, features are extracted from the optimal random image components using greedy approach. These feature vectors are then projected to subspaces for dimensionality reduction which is used for solving linear problems. The design of Gabor filters, PCA and MDA are crucial processes used for facial feature extraction. The FERET, ORL and YALE face databases are used to generate the results. Experiments show that optimal random image component selection (ORICS) plus MDA outperforms ORICS and subspace projection approach such as ORICS plus PCA. Our method achieves 96.25%, 99.44% and 100% recognition accuracy on the FERET, ORL and YALE databases for 30% training respectively. This is a considerably improved performance compared with other standard methodologies described in the literature.     

Electrochemical pretreatment of textile effluents and effect of electrode materials on the removal of organics

The aquatic environment around the textile industries in India was severely affected due to continuous discharge of effluents. In order to avoid further deterioration, the pollution control board of Tamil Nadu, India has enforced zero discharge concepts throughout the state. Consequently, most of the industries have opted membrane technology to recover water. The present study was aimed to find out the efficacy of electrochemical techniques as pretreatment methods to reverse osmosis (RO). The textile wastewater was initially treated by electrocoagulation to remove the suspended solids. After the electrocoagulation, the wastewater was further treated by electrooxidation for COD removal. Mild steel as anode was found to be effective for coagulation of suspended solids. For electrooxidation, graphite and RuO₂/IrO₂/TaO₂ coated titanium were used as electrodes. The efficiency of these electrode materials was evaluated in terms of chemical oxygen demand (COD) removal, instantaneous current efficiency (ICE) and electrooxidation index (EOI). The COD was removed to the extent of 90-93% using graphite and 54% with RuO₂/IrO₂/TaO₂ coated titanium electrodes. The current efficiency of 40% and 11% was achieved with graphite and RuO₂/IrO₂/TaO₂ coated titanium respectively. The degradation of organics was followed using GC-MS and the reason for incomplete degradation of organics in the presence of RuO₂/IrO₂/TaO₂ coated titanium was discussed.     

Keeping smart, omnidirectional eyes on you [adaptive panoramic stereovision]

An adaptive panoramic stereo approach for two cooperative mobile platform is presented. There are four key features in the approach: 1) omnidirectional stereovision with an appropriate vertical FOV, and a simple camera calibration method; 2) cooperative mobile platforms for mutual dynamic calibration and best view planning; 3) 3D matching after meaningful object (human subject) extraction; and 4) real-time performance. The integration of omnidirectional vision with mutual awareness and dynamic calibration strategies allows intelligent cooperation between visual agents. This provides an effective way to solve the problems of limited resources, view planning, occlusion, and motion detection of movable robotic platforms. Experiments have shown that this approach is quite promising.     

Secure Remote User Mutual Authentication Scheme with Key Agreement for Cloud Environment

Authentication schemes are widely used mechanisms to thwart unauthorized access of resources over insecure networks. Several smart card based password authentication schemes have been proposed in the literature. In this paper, we demonstrate the security limitations of a recently proposed password based authentication scheme, and show that their scheme is still vulnerable to forgery and offline password guessing attacks and it is also unable to provide user anonymity, forward secrecy and mutual authentication. With the intention of fixing the weaknesses of that scheme, we present a secure authentication scheme. We show that the proposed scheme is invulnerable to various attacks together with attacks observed in the analyzed scheme through both rigorous formal and informal security analysis. Furthermore, the security analysis using the widely-accepted Real-Or-Random (ROR) model ensures that the proposed scheme provides the session key (SK) security. Finally, we carry out the performance evaluation of the proposed scheme and other related schemes, and the result favors that the proposed scheme provides better trade-off among security and performance as compared to other existing related schemes.

     

Metal-organic frameworks derived spinel NiCo2O4/graphene nanosheets composite as a bi-functional cathode for high energy density Li–O2 battery applications

Electrode materials having a combined heterostructure morphology can boost the electrochemical performance of energy conversion and storage applications. In this paper, we prepared three-dimensional (3D) porous NiCo₂O₄ dodecahedron nanosheets (NCO) from a metal–organic framework template (ZIF-67) and incorporated them with two-dimensional (2D) multilayer graphene nanosheets (GNS) through a simple and rapid ultrasonication process. The combination of these 3D/2D nanostructures created effective interfaces between the NCO and GNS components that enhanced the intrinsic electronic properties and increased the number of active catalytic sites on the NCO@GNS surfaces. Accordingly, the NCO@GNS electrocatalyst displayed superior kinetics for both the oxygen reduction and evolution reactions in both aqueous and non-aqueous electrolytes and could be fabricated into an air-cathode for Li–O₂ battery applications. The NCO@GNS air-cathode delivered a specific storage capacity (7201 mA h g^?1) higher than those of the NCO and commercial carbon black electrodes. We tested the durability of the Li–O₂ battery featuring the NCO@GNS cathode in a new PAT-cell configuration; it exhibited long-term cyclability for 200 cycles with a limited capacity of 500 mA h g^?1 at a current density of 100 mA g^?1. This cathode design featuring meso- and micropores shortened the pathways for Li⁺ ion diffusion and ensured rapid electron and oxygen transfer, thereby increasing the lifetime of its corresponding Li–O₂ battery.     

Dielectric and thermal response of poly[(vinylidene chloride)‐co‐acrylonitrile]/poly(methyl methacrylate) blend membranes

Poly(methyl methacrylate) was mixed with poly[(vinylidene chloride)‐co‐acrylonitrile] (Saran‐F) and lithium perchlorate in tetrahydrofuran to make polymer blend systems. Solvent‐free membranes with various blend ratios were prepared using a solution casting technique. Impedance analysis was used to study the electrical response of the polymer membranes, which shows that the 50:50 wt% blend ratio polymer membrane has a low bulk resistance and high dielectric constant at room temperature and hence high ionic conductivity. The dielectric behaviour was analysed using dielectric permittivity and electric modulus of the samples. The conductance spectra follow the universal power law variation. Structural analysis confirms the amorphous nature and functional group analysis confirms the miscibility. The decomposition temperature of the membranes was determined using thermogravimetric analysis. © 2014 Society of Chemical Industry