Design and Fabrication of Self-Charging Bi-Cycle with Power Saving Application using Solar Panel

With the increase in fuel prices, pollution content in atmosphere and due to gradual end of the nonrenewable sources of energy we have to alter the source of our energy in our vehicles. Now a day’s Bicycles are more commonly used by the youngsters and school students.  At the same time demand of electricity is vital problem in these days and that of the humans becoming tired when pedalling the bicycles to reduce all these problems. We are implementing a self-charging bicycle. The model converts mechanical energy into electrical energy without pollution.

Deep Impression: Audiovisual Deep Residual Networks for Multimodal Apparent Personality Trait Recognition

Here, we develop an audiovisual deep residual network for multimodal apparent personality trait recognition. The network is trained end-to-end for predicting the Big Five personality traits of people from their videos. That is, the network does not require any feature engineering or visual analysis such as face detection, face landmark alignment or facial expression recognition. Recently, the network won the third place in the ChaLearn First Impressions Challenge with a test accuracy of 0.9109

Predicting purchase intention of online consumers using discriminant analysis approach

The Internet plays a vital role in the business world today. It has created a tremendous volume of business transactions all over the world. Internet not only introduces a new way of doing business, it also changes consumer lifestyle. Consumers can buy products or services via the Internet without going to a physical store. Therefore, it is very important to investigate this phenomenon, seeking to determine the variables that actually motivate consumers to adopt internet shopping. In this context, this study attempts to formulate a discriminant equation on the basis of some established predictors and separate the segment into suspects and prospects. It will be healpful for the retailers can make a market assessment about their brand through this approach which will in turn, help the marketer to reduce the market risk.\u

Photocatalytic degradation efficiency of Rhodamine-B for CuO/CdO nanosheets attained through simple co-precipitation method

In the present investigation, the growth of CuO/CdO nanosheets by simple coprecipitation method and characterized by XRD, SEM with EDX, TEM, UV–visible and PL. The incorporation of the non-ionic surfactant Triton X-100 blend with CuO/CdO resulted in hexagonal shaped grains with a nanoporous structure. The pristine CuO and CdO display monoclinic and cubic phases, respectively, whereas the CuO/CdO exhibits a combination of two phases, as proven by XRD analysis. According to TEM analysis the CuO/CdO composite particle size was reduced in the range between 20 and 50 nm resulting, the bandgap value is decreased around 1.26 eV due to size effect. The photocatalytic activity against Rhodamine-B (RhB) showed a 94 % degradation efficiency as compared to pristine CuO (71.42 %) and CdO (77.83 %). Furthermore, the CuO/CdO nanocomposite catalyst dosage increasing the degradation efficiency was found to be 97.62 %. Although the nitration process is more efficient at pH 6, the degradation efficiency for CuO, CdO, and CuO/CdO was found to be 75.74, 85.96 %, and 99.88 % at pH 6. In acidic solution, the reusability of CuO/CdO was outstanding with a 95.80 % degradation efficiency after five successive cycles

Structure, morphology, composition, optical properties of CuO/NiO nanocomposite for electrochemical energy storage devices

A CuO/NiO nanocomposite synthesized using a simple co-precipitation process was employed to produce a high-performance electrochemical supercapacitor. The crystal nature, particle, composition, chemical state, and optical properties were investigated using powder XRD, TEM, EDX, FTIR, XPS, and UV–visible spectroscopy respectively. The electrochemical properties of CV, GCD and EIS are measured in 1 M NaOH. At a 0.5 Ag−1 current density, the CuO/NiO composites exhibit greater capacitance (290.56 Fg-1) when compared to the individual compounds of CuO (165.20 Fg−1) and NiO (190.34 Fg−1). After 2000 cycles the CuO/NiO electrode was excellent 90% of capacity retention. The Ragone plot discovers better energy density of 4.24Wh kg−1 and power density of 10.67 kW kg−1 were provided by the CuO/NiO nanocomposites. The maximal ionic conductivity for the CuO/NiO nanocomposite is 3.56 10-4 S/cm based on the Cole-Cole plot. Furthermore, galvanostatic charge–discharge (GCD), peak current, dielectric properties of dielectric constant and electric modulus are discussed in this work. These results have indicated that the CuO/NiO nanocomposite is an excellent material for supercapacitor electrode construction

Rapid and Scalable Wire-bar Strategy for Coating of TiO2 Thin-films: Effect of Post-Annealing Temperatures on Structures and Catalytic Dye-Degradation

Titanium dioxide (TiO2) thin films were rapidly coated on Corning glass substrates from the precursor solution using the wire-bar technique at the room temperature and then post-annealed at 400, 500 and 600 °C for 1 h under atmospheric conditions. The structural, morphological, optical, wettability and photocatalytic properties of the films were studied. X-ray diffraction analysis confirmed the formation of an anatase TiO2 structure irrespective of the post-annealing temperatures. The optical transparency of the films in the visible range was measured to be > 70%. A water contact angle (WCA) of ~0° was observed for TiO2 thin-film, post-annealed at 400 °C and 500 °C. However, WCA of 40.3° was observed for post-annealed at 600 °C. The photocatalytic dye-degradation using post-annealed thin-film was investigated indicating a steady improvement in the dye-degradation percentage (from 24.3 to 29.4%) with the increase of post-annealing temperature. The demonstrated TiO2 thin-films deposited by wire-bar coating technique showed promises for the manufacturing of large-area cost-effective self-cleaning window glass