Bøger af Lokesh Pawar

A sensor network is a structure that comprised of sensing, computing, and communication elements that provides user the ability to observe and act in response to the events in a specified environment. The user usually belongs to the governmental, civil, industrial entity and commercial. Nodes are scattered in the environment like a biological system, the physical world or an information technology (IT) framework. Sensor systems based on network are seen as the future by observers as it is important technologies that will knowledge applications that are based on these kinds of system in the next few years.

On the basis of this information a vehicle has to take the earlier decision about the path change or to stay with same route. The proposed protocol will also find the alternate optimized path to avoid the accident location. As the accident detected over the network, it will look for the affected area so that remaining vehicles can continue the transmission. The system also defined a low recovery and decision time where the vehicle selects the compromising path that it can select in case of accident. The presented work is being performed in city area with 2 lane system. The results and analysis is done in terms of delay and the data loss over the network.

Data Structure is a way of collection and arrangement of data in such a way that we can perform operations on these data in an effective way. Data Structures is about rendering data elements in terms of some relationship, for better organization and storage. For example, we have data from a university professor¿s name "Tejas" and age 26. Here "Tejas" is a name which comprises of characters into it which collectively formed String which is a data type and 26 is of integer data type and these data types are than stored in memory according to the data structure assigned to the data type.

It took me 2 years to pen it down. I need your 10 minutes to go through this book. I have discussed VANET possibilities of route prediction. A vehicular network is one of the promising areas for research work. Such kind of network suffers from the problem of optimization. This book leads to an intelligent approach to reduce the delay in case of accident. We have defined the network with a new intelligent protocol to perform vehicle to vehicle communication.

Extracting useful information from the pool of big data gives birth to new domain known as Information Extraction. The domain of Information Extraction has its genesis in Natural Language Processing (NLP). The fundamental drift in this field takes the birth from various competitions that are focused on the recognition and extraction of named entities such as names of people, organizations etc. As the world become more data oriented by advent of internet, new applications of processing of structured and unstructured data comes in light. Most of the interest is to extract and classify named entities like person, organization and location etc. that is a subtask of Information Extraction known as Entity Extraction and Classification.

Delay-tolerant networks (DTNs) have the great potential in connecting devices and regions of the world that are presently under-served by current networks. A vital challenge for Delay Tolerant Networks is to determine the routes through the network without ever having an end to end, or knowing which ¿routers¿ will be connected at any given instant of time. The problem has an added constraint of delay at each node. This situation limits the applicability of traditional routing techniques which categorize lack of path as failure of nodes and try to seek for existing end-to-end path. Approaches have been proposed which focus either on epidemic message replication or on previously known information about the connectivity schedule. In this book we have considered that the protocol have the previous knowledge of routing and computed delay on the basis of replication of packets on the nodes and on the basis of total time to transfer the packets from one node to other node. This book puts some light to prevent large delays due to replications and the total time for sending the packets.

The Book is all about our emotion recognization by following matrices and their classification. The results provided in the book are stochastically presented to the readers which is going to give the best output. Spare few minutes to read the book to gain the deep knowledge on emotion recognization using matrices and table. It took several months to reach this destination in emotion recognition. Dr. Jaspreet's help was indeed.