The Tech Fest is a place where a student completes its journey of learning new technologies emerging in the market and come up with new innovative products and creates a new technical era. Tech park over the years has instilled a positive competitive spirit among the engineering students, encouraging them to strive harder and come up with new and better solutions and ideas which make them stand out of the crowd and make their individual identity. Also, the purpose of the event has always been to make students smart and confident with their ideology and thrive them towards a better tomorrow. The continuous effort of enhancement in the skills and learning of the students had been made possible by such events and annual assembly of various departments with the initiative of B.S.A.I.T.M and TECH PARK 2K19 has proved to be one such successful event.

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Ever since the advancement of technology Data is also growing every day, If we go back in time like in 70’s and 80’s  not many people were using computers that’s why data fled into computers was also very less, But now everyone owns a gadget, laptop, mobile phones and generating data every day, every hour and every minute.

There can be several factors for the generation of data. One of the main factors is IOT, leading to the development of smart devices. Another can be social media, We humans are a social animal who love to interact and social media provide what we love, almost every min somewhat 60milions likes and other activities are done leading to the generation of a lot of data. It has been observed that data has been rising exponentially leading to the development of Big Data

Big Data as the named suggest is a large cluster of data but is a problem statement i.e it is an incapability of traditional system to process it. When these systems were created we never thought we have to deal with such amount of data which is produced at high speed and high amount, which traditional system cannot store and process it.

In order to identify Big Data problem, IBM has suggested 5V’S-

Volume– Traditional systems were unable to store and process huge data. Variety-Now a day’s data generated is not in a structured form which traditional system could handle it but they are in a semi-structured and unstructured form which can’t be handled by the traditional system. Velocity– Today data is generated at a very high speed which can‘t be incapacitated. Value– the Traditional system could not find the valuable data among the amount of data. Veracity-Sparse net of data i.e. data we get may not always be correct.

In order to solve all the above problems, an Apache Hadoop Framework is provided which stores and process data set in parallel and distributed fashion. Hadoop is divided into two parts – HDFS  and Map Reduce.

HDFS (Hadoop Distributed File System) provides the storage of data in the distributed environment. It follows the client/server architecture. Where Data is stored in slave nodes (or Data Node) and controlled by Master node (or Name node). In this manner, large data can be stored in different places at the same time and handled by the master controller.

Map reduce-It is a programming unit in Hadoop. This unit uses the advantages of the distributed framework in order to process large data set. It consists of two distinct task one is MAP other is Reduce. Map job produces the key-value pair as an intermediate result which is given to reducer as input producing a single output known as reduced data.

Hadoop uses various tools in order to analyze data like HIVE similar to SQL, PIG, SPARK, LIV etc. these all tools are scalable and reliable. According to need, a tool is selected and data is processed

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MapReduce is a programming model for data processing. Hadoop runs MapReduce programs written in various languages like Java, Ruby, Python, and C++. Most important, MapReduce programs are inherently parallel, thus putting very large-scale data analysis into the hands of anyone with enough machines at their disposal. MapReduce algorithm has been used for applications such as generating search indexes, document clustering, access log analysis, and different other kinds of data analysis as discussed former. A MapReduce job is an access and process-streaming job that splits the input dataset into independent chunks (blocks) and stores them in Hadoop Distributed File System (HDFS). It has two main tasks Map and Reduces, which are completely in a parallel manner. The input phase gives input to the mapper in the <key, value> pairs and then mapper maps these inputs which are partitioned using user-defined partitioning function. The shuffling and sorting of data is made and send to the reducer where reducer then reduces it to optimized form and generates the output.

Programs written in this functional style are automatically parallelized and executed on a large cluster of commodity machines. The runtime system takes care of the details of partitioning the input data, scheduling the program’s execution across a set of machines, handling machine failures, and managing the required inter-machine communication. This allows programmers without any experience with parallel and distributed systems to easily utilize the resources of a large distributed system.

The MapReduce programming model has been successfully used at Google for many different purposes. The success of this method can be attributed for many reasons. First, the model is easy to use, even for programmers without experience with parallel and distributed systems, since it hides the details of parallelization, fault-tolerance, locality optimization, and load balancing. Second, a large variety of problems are easily expressible as MapReduce computations. For example, MapReduce is used for the generation of data for Google’s production web search service, for sorting, for data mining, for machine learning, and many other systems. Third, implementation of MapReduce has been developed that scales to large clusters of machines comprising thousands of machines. The implementation makes efficient use of these machine resources and therefore is suitable for use on many of the large computational problems encountered at Google.

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Develop – right architecture and design for your project.

Implement and instantiate – this design into a working solution.

Deployment software – which meets your requirements as well as budget.

The On-Campus recruitment process initiated with the Deep Logic Tech Team sharing detailed profiles based on student interest and projects received, the team enrolled the profiles as per their eligibility, conducted a Group Discussion and Aptitude Test, followed by interviews by the experienced panel of Deep Logic Tech professionals.
Deep Logic Tech Campus Recruitment helped students in acquiring young talent to nurture and mould them on the basis of organization ideals and art to enable them to become leaders of tomorrow.
Students feel excited to work hard and create results, looking forward to Deep Logic Tech’s opportunities that will aid them in their long-term professional development.
Deep Logic Tech Experts were overwhelmed with the response knowing the interest and zeal of students. Luckily, the couple of students were hired to work ahead after their graduation.

Noteworthy, it was one of the great campus placement drives that every student here at Anangpuria demands!

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Venue: Seminar Hall, Mechanical Engineering Department, BSAITM.

Date: 09 March 2018

One day Seminar was held on “Recent Trend in Design and Development” on 09/03/2018 in the mechanical engineering department of B. S. Anangpuria educational institutes, Faridabad (Haryana).

The Seminar was conducted by Mr.Laxman Tewatia and Mr.A.Yadav (CADD Centre).  Approximately 150 students of 2^nd year and 3rd-year mechanical engineering attended the Seminar. The Seminar was very useful for the Students because it covers the topics like CAD/CAM/CAE Software products for 2D & 3D Modeling. Finite Element Analysing, Detailing and Computer Aided Manufacturing tools.

Mr.Yadav mentioned that mechanical engineering is the broadest of all engineering disciplines that apply the principles of physics and material science for the purpose of product design. Automotive, Aerospace, Marine, Production, Mechatronics, Thermal Engineering, and Robotics are some of the streams that have evolved from mechanical engineering.

This seminar helped the participants to improve the productivity skills and improve their career prospects. After gaining the CAD skills, any mechanical engineers can easily find employment and boost productivity. This program is clubbed with 30 minutes written test, which makes the participant excel and has an edge over the competition.

In the end, Mr. Laxman tewatia, ended the seminar warm thanks. In his thanksgiving the speech, he especially thanked the Hon’ble Director Dr. SS Tyagi for her boosting & enthusiastic involvement & the keen interest in this seminar and Dr. Deepak Khurana (HOD, ME) for sparing their valuable time for the seminar. Similarly, he also thanked all the faculty members and students who actively participated in the seminar & encouraged the organizers.

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Network administrators have often tried their best by improving their network security, however with the rapid surface of new exploits; the best way of ensuring that the system is secure is to attempt penetration testing. This would be the most effective way to find exploits and to proof whether a system is vulnerable. Penetration testing often allows the security analyst to find new vulnerabilities.

“Penetration Testing is the process of validating that the securities of our assets in our entire environment meet the CIA standard as specified by the company.” It is a form of stress testing, which exposes weaknesses of flaws in a computer system. It is more art of finding an open door from where the attack is possible.

Penetration testing is a testing technique for discovering understanding and documenting all the security holes that can be found in a system. It is an authorized attempt to violate specific constraints stated in the form of a security or integrity policy. It is a test for evaluating the strengths of all possible security holes and provides suggestions for fixing them. This testing typically includes network penetration testing and application security testing as well as controls and processes around the networks and it should occur from both outside the network trying to come in (external testing) and from inside the network(internal testing).

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