This paper presents a new sorting method for acrylonitrile-butadiene-stryrene (ABS) and poly styrene (PS) by means of microwave cavity resonator perturbation. In this method, a small piece of sample material is inserted into a cavity resonator at a point when the electric and magnetic fields mark the maximum and the minimum values, respectively. Experiments were carried out with use of 1-, 2-, 5-, and 10-GHz resonators and ABS and PS samples of various sizes. Loss angles of polarizability (tan χ) exhibited differences large enough to achieve accurate sorting between ABS and PS.

Big data management (BDM) is the administration, management and governance of large volumes of all types of structured, semi-structured and unstructured data. Big data management is a blend of old and new best practices, teams, data types, skills, and home-grown or industrial-built functions and methods. Big Data Management is at the genesis of massive change to technology that will spur massive societal and industrial change. In this paper, different key factors kept in mind while managing big data are discussed along with the process of managing data so that organisations can get secure and accurate data. Further different developers have introduced methods have also been discussed and with it the main tools used in management of Big Data are introduced in this paper. BDM is suffering from many issues in the world are also explained here. Big Data Management deals with the integration, manipulation, quality and governance and management of Big Data including the key factors- Volume, Velocity and Variety of Big Data.

Network insecurity has become an increasing problem in the world of computer networks. Technical experts have tried to combat this by improving the technical awareness of the threats and technical solutions involved in Wireless Local Networks (WLAN) through technical reports and policy enforcement. The average users' knowledge and awareness of network security, how they react to the warnings and implement security measures is also very important. Current studies on users' awareness of security policies, whether it has been communicated well enough and how aware WLAN users are to the threats and issues involved are still not fully ascertained. To fill this gap it is important to find out the users basic knowledge of the security measures and policies. In this paper, statistical methods were developed and adopted in other to compare the knowledge of Information Technology (IT) related employees and that of non-technical employees on how aware they are of WLAN security threats and security measures. The techniques the paper has adopted revealed the knowledge gap between non-technical and technical users. This revelation is significant and therefore requiring more efficient methods for creating awareness on WLAN threats and countermeasures among average users.

In this era of increasing technological advancement, where mankind is pushing the frontiers of exploration, systems are required to be increasingly autonomous and intelligent in order to work efficiently, and to provide optimum results. Unmanned vehicles generally use GPS to find their position in an environment and navigate. In this paper, we have studied and analysed two different algorithms used for navigating in a GPS denied environment, which is a more common scenario than navigating in a GPS-enabled environment. The SLAM algorithm generates a map of its environment by estimation and mapping, while the LIDAR maps its environment using pulses of a short wavelength. Both of them can be used for widely varying applications, and current researches in these fields are crucial in the development of autonomous systems.