Earticle

In recent times, malicious objects have significantly increased in volume by many folds. Firewall, anti-virus (AV) or signature based intrusion detection systems (IDSs) all are found effective but only for known malicious objects. In that sense, unknown malicious objects are more dangerous. There are many techniques like honeypots, honeynets or anomaly based IDSs which are capable enough to identify these new malicious objects. This paper introduces a technique to develop a library not only for past and present attacks but also for future attacks, so that signature based IDSs not only detect known malicious objects but the unknown and future malicious objects as well. In our approach, with the help of a series of four algorithms, we show a way to develop all possible variants of each detected malicious object and finally update the library with these variants in order to empower it with future attacks.

The discrete elements code CeaMka3D uses cells of Voronoï as particles. Having clarified the expression of forces and torques in the elastic formulation, the concepts of volume of rotation and of volumetric vector of bending are introduced to simulate the bending. Some simulations of plates illustrate the capacity of this formulation.

The banking sector plays a very vital role in the economic development and growth of a country. The effective and efficient banking sector is thus the fundamental requirement for smooth functioning of any economy. In the present study an attempt has been made to assess the technical efficiency and performance of Indian Banking Sector. This study uses DEA approach to estimate the technical efficiency of commercial banks in India over the years 2009-2014. Data Envelopment Analysis (DEA) is widely used in banking sector to measure the efficiency and performance of the banks. The study is based on top 24 Indian commercial banks (6 public, 6 new private, 6 old private and 6 from foreign sector banks). The results of the study indicated that old private sector banks and foreign sector banks were found more efficient than new private sector banks, whereas new private sector banks did not use their IT inputs well. In consideration of scale inefficiency analyzed that foreign sector banks have done well in the field of using their input efficiently than other banks.

The Design and Implementation of a model contactless smart card railway ticketing solution is presented in this paper. An appropriate ticketing system is one of the necessary means to ensure optimal revenue collection as a rail station operator. In Nigeria, manual ticketing involving plain paper tickets are still in use as at the time of this research. This system has many disadvantages which include the difficulty in tracking sales, very poor access control, difficulty in offering benefits to customers and the high cost of providing security for the trains. The system proposed is easy to use and manage. It makes use of the Contactless Smart MIFARE S50 card which has a three – step authentication method and also has 15 sectors to allow for use in multiple applications apart from rail transport ticketing. A model to show how the system will work was implemented using the Intel Galileo Generation 1 Board as the controller.

The light weight hybrid composites are the most promised materials of the today’s engineering world. They have high strength to weight ratio and they find wide range of applications in aviation and automobile sectors. The production of these potential hybrid composites is cheaper when the selected reinforcements are economical. The aim of the paper is to investigate the mechanical properties on Al356.2 alloy reinforced with locally available inexpensive rice husk ash & fly ash reinforcements. The effect of these reinforcements on the mechanical properties of Al356.2 were studied at 4:6, 5:5 and 6:4 weight% of Fly Ash (F.A) and Rice Husk Ash(R.H.A) respectively. The reinforcement’s F.A and R.H.A are added to Al356.2 through stir casting technique. Interesting facts brought into light that the hybrid cases have prominent mechanical properties than pure Al356.2 alloy.

Photovoltaic (PV) power prediction, as a necessary technical requirement of PV plants, closely relates to the accuracy and rationality of power grid dispatch. If the output power of PV plants can be further enhanced by forecasting, the risk of grid-connected will be greatly reduced, and the safety and stability of power grid will be increased. Therefore, we propose a novel short-term forecasting model of output power based on the MEA-BP, which is optimized by Mind Evolutionary Algorithm (MEA) and Back-Propagation (BP) neural network. We focus on the actual operation of 100MW large grid-integrated PV station, which takes the important meteorological factors and historical generation data of PV station. In our research, the prediction problem includes four units according to different seasons, different data, and the output of PV station respectively. The experimental results show the prediction accuracy in different prediction units. The proposed MEA-BP model efficiently reduces the prediction errors compared with the traditional BP model.

A numerical simulation was performed to study the heat transfer performance of a hot fluid in a confined impinging jet on a flat heated surface. The tests were realized for the following ranges of the governing parameters: the jet thickness is 2m and the distance of horizontal jet to heated surface was set to 1 to 3 m. Three different cases are considered in this analysis. They are H/D = 0.5,1 and 1.5. Fluids like Acetylene and Acetyl chloride are compared in this analysis. Turbulent models considered for this analysis are Spallart Almaras, k-ω and k-ε. Out of these three k- ω model gives more heat transfer characteristics. The plate is considered to be stationery. Horizontal Jet with convergent nozzle is considered and compared in this analysis. Finally we found out that Surface Nusselt number, Surface Heat Transfer coefficient plays vital role for better heat transfer calculation.