Around the globe, scientists and researchers are discovering new methodologies and techniques to download the data stored in the brain of a dead person for its further utilization. After the clinical death of the body, the scientists would use intelligence of any person in the form of blue brain which is also called as virtual or artificial brain that works actively when inserted as robotics machine. The paper presents the synergetic interaction between man and machine having master-slave relationship where a man act as a master and nano-robot act as slave. The nano-robot uses sixth sense technology device for mind mapping utilizing blue brain with swarm intelligence. The benefit to utilize swarm intelligence is to provide social interactions with the environment and utilizing the blue brain benefits for restoration of knowledge, memory and past experiences of a person for the further development of society. The collaboration between man and machine intelligence leads to achieve a smart or intelligent joint action for developing projects in any industry or daily life works. KeywordsNano-robot, sixth sense, blue-brain, swarm intelligence.

This paper presents analysis of methodology proposed for mutual interaction among human and robotics following master slave relationship using three different types of interaction modes viz. co-existing, conditional and essential mode. These different modes of interaction during the performance of any desired task may include time for entering into the task, task processing time and task completion period. The collaboration between human and robotics leads to achieve a joint action for its utilization in developing projects in any industry and other daily life work. The technique designed in this paper helps human and robotics to handle queries and tasks using human robotics in such a way that robotics/human acts as an interface with the server system for the flow of communication data. The proposed procedure describes the way of humans interaction with the robotics and shows the complete communication flow among them either by using input in continuous (analog form) or in discontinuous (digital form). For providing more reliable and safer environment during communication, IVRE (Immersive virtual robotics environment) may be used with the help of virtual reality in virtual environment system.

Human-robotics interactions generally consist of transfer of information from the humans to the robotics by using various algorithms, scientific tools and techniques. In this research paper human queries and tasks can be handled by human robotics and for the communication with the server-systems robotics acts as an interface. Human queries can be easily recognized with the help of data mining techniques. These Queries can be handled into three different parts. (a)Input device-used to collect the data (b) Human Robotics-act as an interface (c) Server System-used to process data. In the absence of interface interactions between the human and server system will not be possible. Here we are uses three types of data mining techniques like Classification, regression analysis and time series analysis. Each technique uses a separate type of data to perform mining task. The special focus of this paper is human and robotics follows master-slave relationship and ultimately humans successfully collaborate to achieve a joint action.

Due to its distinct and unique features viz. high speed data rate, self-organized network, packet optimized radio access, low latency and flexible bandwidth deployment LTE (Long Term Evolution) is more preferred in wireless communication. Such kind of terminology uses especially in mobile phones for improving its throughput. LTE uses Orthogonal Frequency Division Multiplexing (OFDM) for the downlinkthat is, from base station to the terminal to transmit the data over many narrow band carriers each of 180 KHz instead of spreading one signal over the complete 5MHz career bandwidth. The complete working of LTE is based on the basic principle of OFDMA (Orthogonal Frequency Division Multiplexing). At first step, it divides the broad spectrum into multiple narrow bands and transmits information on this narrow channel in parallel.OFDM meets the LTE requirement for spectrum flexibility and enables cost-efficient solutions for very wide carriers with high peak rates.Orthogonal frequency-division multiplexing (OFDM), is a frequency-division multiplexing (FDM) scheme used as a digital multi-carrier modulation method. Scheduling plays a vital role on the time of resource allocation which has become an essential component for high-speed wireless data systems. This allocation of resources is done according to the need and priority of the user. It has three key components which are involved in the resource allocation and network optimization: resource block scheduling, power control, and client association. The motive to design this new designed methodology is to increase its privacy rate by increasing its security level that automatically improves its speed and data rate. LTE uses OFDM (orthogonal frequency division multiplexing) for downlink transmission. In resource allocation algorithms in OFDM of LTE systems, the allocation of the radio resource has to be in the units of Scheduling Block (SB) and there exists the need for all SBs of each user to use the same Modulation and Coding Scheme (MCS) leading to the degradation of performance. Main challenge for LTE systems is that, by applying OFDMA, multiple resource blocks can be scheduled by a transmission over the frequency and time. In this research paper, we have to focus on resource block scheduling in LTE system and proposes an enhanced version of Na Gaun technique that would be helpful for resource allocation blocks so that user's rate requirement can be fulfilled optimally and throughput of the system can be improved.

Ambient Intelligence in the modern era of research and innovations is an active field that uses various embedded computing devices for providing different types of interaction with environment. This paper describes a new methodology "Faculty Performance Monitoring Scale" abbreviated as "FPMS" aiming to improve the overall quality of existing education system utilizing an application of ambient intelligence. As designed, the methodology elaborates the mutual interaction among humans and service robotics having master-slave relationship in which humans act as a master and service robotics act as a slave. Human utilizes interface embedded in service robotics for giving instruction and service robotics will respond according to the instruction given by the master. The primary duty of service robotics is to store and monitor the faculty members at the time of lecture delivery and calculate their performance on the basis of certain parameters as considered in FPMS. The benefit to utilize this designed methodology is to reduce conflicts among faculty based upon biases' and appreciation will be given on the basis of feedback from FPMS. An appropriate collaboration between human and service robotics leads to achieve a joint action and provides a mechanism of active team participation utilizing a more natural form of interactions. The proposed architecture design has been compared with the current education system and may be followed by the educational institutes for maintaining efficiency as the case thereof.