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Human societies have always devised codes or rules to live by. These codes or rules are set in place to ensure the overall well-being of most of the people. But we cannot deny the fact that crime has always manifested itself by one way or another and can be traced back to as far in history as records go. The origin of crime can be traced to combination of various social, economic, demographic institutional and local factors. These factors contribute towards various aspects of an individual’s life such as his education, employment, family relationships, emotional stability, mental health, anonymity etc. which play a huge role in further determining the nature, pattern, frequency and volume of crime. So, until now we have established that where there are human society’s crime and criminals are inevitable. The major problem which arises is that in some underdeveloped or developing countries crimes of all nature are not talked about openly or acknowledged let alone be reported. People as individuals should be equipped to their best of abilities in order to protect themselves and their families from all possible aspects of what they perceive as evil and to do so we will use Liner search, Dijkstra’s and A* algorithm for finding the convicts near you.

Cloud computing is the modern technology, that facilitates to the user various resources, data and files to access from anywhere that a network is available, it is today’s modern computing where we distribute our resources and software from one place to another, but still the security of the data is a major problem in the cloud. However, there is need of processing a huge number of data and maintained the security over cloud. In this research we proposed a software framework (hadoop) with the cloud which helps us to process the huge number of data by using map-reduce model. To add security we use Kerberos authentication protocol which helps us to enhance security level over the cloud and also it is used to provide authentication to the users. We analyze and compare our technique with existing techniques, the results shows that our technique is much more secure and provide user authentication.

Intelligent Systems or Smart Systems plays an important role in our day to day life. Deep learning (DL) is portray day by day a key role in our lives. It makes our work easier and efficient. It has already made a colossal impression in different areas, like cancer treatment diagnosis, in the quality of inventing new antibiotic, self-driving cars, foretelling of precognition and speech recognition. The meticulous domestic characteristics remover used in conventional knowledge, classification, and pattern recognition systems are not adaptable for massive-sized data sets. In many situations, confide in on the problem complication, DL can also beat the shortcomings of prior trivial networks that hindered productive training and thinking of hierarchical portrayal of multi-dimensional training data. A lot of parts of units comprised with enhanced algorithm and architecture used by DNN. The current survey retrospect’s a few optimization methods to boost the perfection of the training and to decrease time of training. We leave no stone unturn into the math back of training algorithms used in current deep networks. We define current shortcomings, enhancements, and implementations. The survey also canvas distant types of planning like intricacy networks, deep learning networks, frequent neural networks, increase learning areas & patterns variation auto encoders that aims to learn depiction for a set of data, typically for dimensionality contraction, by practicing the network to avoid signal “noise’’ and others.

Specially appointed remote systems made of versatile stations that transmit information over a typical remote channel, along these lines are shaping an all-remote correspondence arrangement. In contrast to cell/wired systems, the portable stations are not upheld by a pre conveyed foundation. For example, base stations, a wired spine, a focal system station, and so forth. Subsequently, the foundation of the system structure and its operational execution must be only over the remote medium, and in a dispersed and decentralized way. With the conspicuous innovative difficulties, these systems have pulled in noteworthy research enthusiasm for ongoing years, as they are very appropriate for some trying settings, for example, in pursuit and salvage tasks, detecting applications, work systems, vehicular interchanges, and so forth. Here in this paper, we present the idea of remote impromptu systems; we talk about their points of interest and the reasons which debase the execution of specially appointed systems and significantly diminish the throughput of the system and increment the crash and postponement of the systems in particular “Hidden” and “Exposed” station issue. We have employed a twofold busy tone build Medium Access Control methodology to totally alleviate these problems. Reenactment results demonstrate the exactness of our proposed plan as far as higher throughput and lesser crash rate.

Regression analysis is an important tool for modeling and analyzing data. Here, we fit a curve / line to the data points, in such a manner that the differences between the distances of data points fro m the curve or line is minimized. As given in our paper their there is comparing between Lasso and Ridge, In our work we will introduced one more method and show their comparison, so before implementation let’s see some of the factors which are involve during this research. Keyword- Regression, Lasso, Ridge, SVM, and KNN

Web caching and restoration are the most common techniques that play a key role in improving web performance by keeping web objects that are likely to be visited in the near future closer to the custo mer. Web caching can work independently or in combination with Web pre-fetching. Cache and Web fetching can complement each other as the temporary Log file is a crucial part of web application. The log analysis is an important issue for the web application. Log file is not to be over emphasized as a source of information in systems and network management, whereas conduct efficient investigation and gathering of useful information need to correlate different log file. Task of analyzing event log files with the ever-increasing size and complexity of today's event logs has become cumbersome to carry out manually. Nowadays latest spotlight is automatic analysis of these logs files. Analysis of Web log is an innovative and unique domain constantly formed and modified by the convergence of several emerging web technologies. Because of its interdisciplinary nature, the diversity of issues addressed, the variety and the number of Web applications, is subject to many different methodologies. Proposed methodology has been used as effective web pre-fetching technique for frequent page generation by using relative position by inter session gap. The fast and efficient web pre-fetching scheme has improved user response of web page and expedites users visiting speed. Keywords: Web mining, web caching, web prefetching, Clustering, Client server Architecture, Log File.