Investigation on multiferroic properties of BiFeO3 ceramics

BiFeO₃ polycrystalline ceramics was prepared by solid-state reaction method and its structural, optical and magnetic properties were investigated. BiFeO₃ was synthesized in a wide range of temperature (825–880 °C) and a well crystalline phase was obtained at a sintering temperature of 870 °C. X-ray diffraction patterns of the samples were recorded and analyzed for the confirmation of crystal structure and the determination of the lattice parameters. The average grain size of the samples was found to be between 1–2 μm. The determined value of direct bandgap of BiFeO₃ ceramics was found to be 2.72 eV. The linear behavior of M-H curve at room temperature confirmed antiferromagetic properties of the BiFeO₃ (BFO). S shaped M-H curve was obtained at a temperature of 5 K. In the whole temperature measurement range (5–300 K) of M-T, no anomalies were observed due to high Curie temperature and Neel temperature of the BiFeO₃.     

The use of pretreated palm oil mill effluent for acetone–butanol–ethanol fermentation by Clostridium saccharoperbutylacetonicum N1-4

Palm oil mill effluent (POME) was used as an acetone–butanol–ethanol (ABE) fermentation medium using Clostridium saccharoperbutylacetonicum N1-4. Various pretreatment methods were applied on POME to increase the amount of fermentable sugars leading to enhanced ABE production. Sulfuric acid-treated POME (SA-POME) method was found to give the highest yield of total reducing sugars (glucose, cellobiose, xylose, and arabinose) as compared to other pretreatment methods. An increment in the concentration of H₂SO₄ from 1 to 2% resulted in the enhanced release of reducing sugars (18.3, 26.3?g/L, respectively). However, the treatment of POME with 3% H₂SO₄, decreased the reducing sugars to 21.6?g/L and consequently, the total ABE production was also reduced. The highest yield of ABE was observed from a culture grown with POME treated by 1% H₂SO₄. The total ABE production from 1, 2, and 3% SA-POME was obtained as 2.2, 0.45, and 0.41?g/L, respectively. Although, enzymatically treated POME (EH-POME) could produce 4.42?g/L glucose, sulfuric acid treatment (1%) was able to liberate only 1.76?g/L glucose, ABE production was higher when 1% SA-POME was used. Low yield of ABE from enzymatically treated POME can be attributed to the production of some inhibitors during hydrolysis of POME. When EH-POME was treated with XAD-4 resin to nullify the inhibitors, the production of ABE was increased to 4.29?g/L, and ABE yield was also increased to 0.29?g/g. In conclusion, enzymatic hydeolysis of POME followed by elution to XAD-4 column can be proposed as the best pretreatment method for highest productivity of ABE. It was found that addition of P2 medium to the POME hydrolysates was able to improve the production of butanol except in raw POME and sulfuric acid hydrolysates.     

Anomaly Based Camera Prioritization in Large Scale Surveillance Networks

Digital surveillance systems are ubiquitous and continuously generate massive amounts of data, and manual monitoring is required in order to recognise human activities in public areas. Intelligent surveillance systems that can automatically ide.pngy normal and abnormal activities are highly desirable, as these would allow for efficient monitoring by selecting only those camera feeds in which abnormal activities are occurring. This paper proposes an energy-efficient camera prioritisation framework that intelligently adjusts the priority of cameras in a vast surveillance network using feedback from the activity recognition system. The proposed system addresses the limitations of existing manual monitoring surveillance systems using a three-step framework. In the first step, the salient frames are selected from the online video stream using a frame differencing method. A lightweight 3D convolutional neural network (3DCNN) architecture is applied to extract spatio-temporal features from the salient frames in the second step. Finally, the probabilities predicted by the 3DCNN network and the metadata of the cameras are processed using a linear threshold gate sigmoid mechanism to control the priority of the camera. The proposed system performs well compared to state-of-the-art violent activity recognition methods in terms of efficient camera prioritisation in large-scale surveillance networks. Comprehensive experiments and an evaluation of activity recognition and camera prioritisation showed that our approach achieved an accuracy of 98% with an F1-score of 0.97 on the Hockey Fight dataset, and an accuracy of 99% with an F1-score of 0.98 on the Violent Crowd dataset.     

Mining Software Repository for Cleaning Bugs Using Data Mining Technique

Despite advances in technological complexity and efforts, software repository maintenance requires reusing the data to reduce the effort and complexity. However, increasing ambiguity, irrelevance, and bugs while extracting similar data during software development generate a large amount of data from those data that reside in repositories. Thus, there is a need for a repository mining technique for relevant and bug-free data prediction. This paper proposes a fault prediction approach using a data-mining technique to find good predictors for high-quality software. To predict errors in mining data, the Apriori algorithm was used to discover association rules by fixing confidence at more than 40% and support at least 30%. The pruning strategy was adopted based on evaluation measures. Next, the rules were extracted from three projects of different domains; the extracted rules were then combined to obtain the most popular rules based on the evaluation measure values. To evaluate the proposed approach, we conducted an experimental study to compare the proposed rules with existing ones using four different industrial projects. The evaluation showed that the results of our proposal are promising. Practitioners and developers can utilize these rules for defect prediction during early software development.     

Algorithms for generating large scale nonlinear programming problems with known degree of difficulty

Convex-quadratic functions are defined based on real symmetric positive definite matrices. Gershgorin's Theorem is used for randomly generating positive definite matrices of arbitrary size. A computational algorithm is presented. The concept of degree of difficulty of a test function is introduced and it is used to define an algorithm to generate test problems with varying degree of difficulty. These algorithms when used in conjunction with the Rosen and Suzuki method may be used to generate large scale constrained nonlinear programming problems.     

DFT studies of thermoelectric properties of R–Au intermetallics at 300 K

Thermoelectric and electronic properties of cubic bi-intermetallics R-Au(R = Tb, Ho. Er. Tm and Yb)compounds were explored. Electronic properties i.e. density of states and band structure were computed using first principles calculations which proved the metallic nature of these compounds. Post-DFT(BoltzTraP) calculations were carried out to explore their thermoelectric properties like electrical conductivities. Seebeck coefficient, electronic thermal conductivities and figure of merit. The highest Seebeck coefficient and figure of merit were found for YbAu among these compounds which are 105 μV/K and 0.285 respectively. All the calculations were carried out at 300 K. Large values of figure of merit obtained for these compounds at room temperature indicate that these materials can be used for thermoelectric devices however need experimental verification.     

Insights into cadmium induced physiological and ultra-structural disorders in Juncus effusus L. and its remediation through exogenous citric acid

This study appraised cadmium (Cd) toxicity stress in wetland plant Juncus effusus, and explored its potential for Cd phytoextraction through chelators (citric acid and EDTA). Cadmium altered morphological and physiological attributes of J. effusus as reflected by growth retardation. Citric acid in the presence of 100 μM Cd significantly countered Cd toxicity by improving plant growth. Elevated Cd concentrations reduced translocation factor that was increased under application of both chelators. Citric acid enhanced Cd accumulation, while EDTA reduced its uptake. Cadmium induced oxidative stress modified the antioxidative enzyme activity. Both levels of citric acid (2.5 and 5.0 mM) and lower EDTA concentration (2.5 mM) helped plants to overcome oxidative stress by enhancing their antioxidative enzyme activities. Cadmium damaged the root cells through cytoplasmic shrinkage and metal deposition. Citric acid restored structure and shape of root cells and eliminated plasmolysis; whereas, EDTA exhibited no positive effect on it. Shoot cells remained unaffected under Cd treatment alone or with citric acid except for chloroplast swelling. Only EDTA promoted starch accumulation in chloroplast reflecting its negative impact on cellular structure. It concludes that Cd and EDTA induce structural and morphological damage in J. effusus; while, citric acid ameliorates Cd toxicity stress.     

Numerical Evaluation of Compound Poisson Distributions

A useful interpretation is applied to probability generating functions for discrete random variables in order to provide an algorithm for calculating probability mass functions for compound Poisson distributions. This interpretation involves a theorem for geometric transforms which is developed to provide a method for calculating the inverse transform of exp (az^k). The result of this theorem is then applied to formulate an algorithm for numerically inverting the geometric transform of a compound Poisson process. The evaluation of these probabilities may be carried out to a prespecified point with an accuracy dependent only on the accuracy of the input distributions. The procedure is illustrated by the numerical calculation of the distribution of daily demand probabilities required in the analysis of an inventory system.