Dr Anuranjan Misra
@gniotgroup.edu.in
Dean Research and Development
Greater Noida Institute of Technology Greater Noida
1. Working as Professor & Dean (Research, Innovation & Development) at Greater Noida Institute of Technology, Greater Noida.
2. Innovation Ambassador , Ministry of Education, Govt of India
3. 21 Years of Experience in Academics, Research & Industry.
4. Authored published 140 research papers and authored 42 books.
5. 1 International and 5 National Patent published .
6. Mission 10 X certification by Wipro, India, IBM certification on IT Infrastructure Management, India, Microsoft Technology Associate certification by Microsoft corporation USA, Infosys certification for Campus Connect Training by Infosys , India.
7. An Alumnus of IIM, Calcutta, GGS IP University, Delhi
8. 8 students had completed PhD on topics link Big Data, Cloud Computing, Artificial Intelligence, Machine Learning
9. Chairman, Computer Society of India, Ghaziabad Chapter
10. Senior Member of ACM, CSI, IACSIT, IACNG, IRACST, CSTA, ISOC, ICE, AEE, IFETS, ISMCDM, SIGSE.
EDUCATION
Professional Qualification: BS, Integrated MS, M.Tech(CSE), PhD , FIIE
Interdisciplinary Qualification: LL.B, LLM(Cyber Law & IPR), EPBCL from IIM Calcutta
RESEARCH INTERESTS
Big Data, Cloud Computing, Software testing
Scopus Publications
Scopus Publications
Sonam Kumari, Anuranjan Misra, Amitabh Wahi, and Pramod Singh Rathore
IEEE
Wine is an alcoholic beverage made from different varieties of grapes after fermenting of grapes. There are different styles of wine varieties depends upon types of grapes used (with or without peeling of skins of grapes) and strains of yeast like red wine, white wine, rose wine, orange or amber wine. Wine can be made from others fruits, grains, cashew coconut, honey etc. Quality and taste of wine depends upon making process and aging of wine. Top 3 Wine producer countries in world are Italy, Spain, and France as per 2021 report. Red wine contains 5.5 to 20.5% of alcohol in it. Consumption of Red wine in right amount is good for health but consumption in large amount is bad for health. The quality of red wine may be predicted by using artificial intelligence techniques with the help of different chemicals parameters as attributes. In this paper, red wine datasets were used for training and testing purpose for the classification of red wine into 6 categories. 6 classes of data were converted into two class based on the quality index. Four different approaches of machine learning algorithms were applied to predict the classification of red wine on two class datasets. It was found that out of four algorithms, the decision tree classifier predicted better performance result of red wine quality compared to other machine learning classifiers.
Divya Mishra and Anuranjan Mishra
Springer Singapore
Kamalpreet Bindra, Anuranjan Mishra, and Suryakant
Springer Singapore
Kamalpreet bindra and Anuranjan mishra
IEEE
The foremost illustrative task in data mining process is clustering. It plays an exceedingly important role in the entire KDD process also as categorizing data is one of the most rudimentary steps in knowledge discovery. It is an unsupervised learning task used for exploratory data analysis to find some unrevealed patterns which are present in data but cannot be categorized clearly. Sets of data can be designated or grouped together based on some common characteristics and termed clusters, the mechanism involved in cluster analysis are essentially dependent upon the primary task of keeping objects with in a cluster more closer than objects belonging to other groups or clusters. Depending on the data and expected cluster characteristics there are different types of clustering paradigms. In the very recent times many new algorithms have emerged which aim towards bridging the different approaches towards clustering and merging different clustering algorithms given the requirement of handling sequential, extensive data with multiple relationships in many applications across a broad spectrum. Various clustering algorithms have been developed under different paradigms for grouping scattered data points and forming efficient cluster shapes with minimal outliers. This paper attempts to address the problem of creating evenly shaped clusters in detail and aims to study, review and analyze few clustering algorithms falling under different categories of clustering paradigms and presents a detailed comparison of their efficiency, advantages and disadvantages on some common grounds. This study also contributes in correlating some very important characteristics of an efficient clustering algorithm.
Shruti Garg and Anuranjan Misra
IEEE
Information Technology is an integral part of the industry for a long time and the role of Services has increased in last 10 years. IT had been playing a major role in the Manufacturing sector in the first half of the decade, which now has shifted to the Services. With this shift in focus of the industry, from Manufacturing to Services, there arises a need of certain set of policies and standard procedures, which help the organizations in providing up to the mark services to their customers, and improved customer relations. Information Technology Infrastructure Library (ITIL) is such a set of best practices and standard procedures, which helps in practicing better Information Technology Service Management (ITSM). This paper studies some of the benefits of the Service Operations process named Incident Management of the ITIL and highlight its best practices. The paper will give a detailed description of Incident Management from the User perspective, as well as from the Administrator and Developer perspective. The automation of this out-of-box vendor-provided process can help the users in using the ITSM tools more efficiently. This paper also studies the benefits of hosting the servers on Cloud as well as how it may help in using the ITSM tools on the go.
Suyash Mishra and Anuranjan Misra
IEEE
The volume of data in the world is growing very fast and generated from verity of sources like social media, sensors airline industry or scientific data in different formats. Biggest challenge is how to infer meaningful insights from such a varietyful and big data along with concern of data storage and management of fast growing data. The size of the databases used in today’s enterprises has been growing at exponential rates day by day. Hence, industries requirement to quickly process and analyze the big data volumes for business decision making and customer insights has also grown exponentially. Data pouring from various sources may be can be structured or unstructured in nature. Structured data refers to a relatively well-organized information, which can be further inserted into traditional RDBMS. As Traditional RDBMS are efficient and easy queries by simple, straightforward search algorithms or SQL queries. In contrast to structured data, unstructured data can be considered as information, which does not, comes in a pre-defined data format, well organized data storage model, or cannot be stored well into relational tables. It is assumed to be fastest growing type of data, e.g. image, sensors data, web chats, social networking messaging data, video, documents, log files, and email data. There are many techniques and software available, which can process and provide efficient storage of unstructured data and help organization to perform analytics on unstructured data. Unstructured data does not well-organized and not stored in predefined manner e.g. logs, web chats. The variety and on ordered nature of data makes storage methods and structure makes execution a time and resource-consuming affair. Advancement into technology has open floodgates to push huge volume of unstructured type of data. Multimedia data is one of the example of unstructured big data, which spans all over the Internet. This needs high execution capability to extract useful information. Rapid processing of multimedia data such as video is important for e.g. criminal investigations, surveillance monitoring, news analysis, sports analytics domain, emotion extraction, etc. Hence, analysis of multimedia data in minimum timeframe is one of the latest research areas. Therefore, we have researched techniques for analyzing unstructured data to extract meaningful information hidden in the big data. In addition, we will describe about various techniques and software used to Manage, process unstructured big data in efficient manner, and increases the performance of complexity analysis.
Preeti Johri and Anuranjan Misra
IEEE
The study of this paper of ours is focused on assessing the K-12 students since this is the major portion of student’s life and whatever they are going through during this tenure stays in their memories and plays a vital role in their life. Here, we have tried to elaborate how and what impact the non–cognitive factors leaves on the students who are going though the K-12 education system. Non–cognitive factors consists of the impact of Psychological factors, Motivational factors, Environmental surroundings, Amenities and facilities available which can transform experiences of students, deciding and achieving goals, improvement in their academic patterns, orientation towards social responsibilities etc. We will also be discussing the educational initiatives and interventions that may be “Motivation”, “Praising”, “Appraising”, “Encouragement”, etc.
Anuranjan Mishra and Naina Pal
IEEE
Joint clustering of multiple networks has been shown to be much more accurate when compared to the clustering on individual networks performed separately. For joint multi-network clustering, many multi view and multidomain network clustering methods have been proposed. These methods assume that there is a common clustering structure which is shared by all networks, and different networks can provide complementary information on the underlying clustering structure. Better clustering performance can be achieved by considering the groups differently. As a result, an ideal method should be able to automatically detect network groups so that networks which are in the same group share a common clustering structure. To address this problem, we propose a novel method, K-means to simultaneously group and cluster multiple networks.
Anuradha, Somesh Kumar, and K. Rama Krishna
IEEE
Rapid growth of technology make possible use of many types of data. Reduced costs of communication charges and many electronic gadgets is leading to increase in the number of users and hence generation of large volumes of data over public networks. Consequently security breaches and threat to information security is major issue of concern. Encryption methods play a key role in providing security. Advanced Encryption Technique is proven to be one of the best methods for text encryption. Image pixels being highly correlated, demand strong and variant encryption methods. In this paper a variant of AES algorithm is presented which ensures security and resistant to various Cryptanalysis.
Preeti Johri and Anuranjan Misra
IEEE
Through this paper of mine I would like to elaborate the usage of Digital Technology in classrooms. In many countries teachers as well as students are allowed to use the newly introduced devices like iPad, Tabs, Minis and etc with WiFi connectivity at the school levels. In India still we are struggling with the old anomalies of not even using the electronic devices which are generally used in terms of technology advancement. The usage of such devices at the school level can help and provide the knowledge to students to compete in the technology world. These devices are capable enough to become the guide and the mentor to make students techno savvy which will play a vital role in making the education system fully ICT based at school levels.
Manoj Kumar Singh and Anuranjan Mishra
IEEE
Our law enforcing system called as Indian Legal System is lacking in terms of computerisation intelligent enough to enable law open for everybody. We are moving towards Digital India in all spheres of activity. In our country majority of people are not aware of the law of the land. AKOMA-NTOSO is an international technical standard for representing judiciary documents in addition to executive & legislative in a structured manner. We can call it XML vocabulary on law and it suggests also a convention of giving name for providing unique identifier to legal sources based on FRBR mode. There is no effort has been made to create standard representation of law in India. The subject matter of the paper goes into detail of creation of standard representation of parts of RTI Act 2005 for its implementation under a given circumstances. The process model of second appeal was undertaken. It was found that majority of RTI appeals at CIC are returned only for the reason that rule 8 and 9 of the RTI Act has not been fulfilled. The study captured the process of filing second appeal and created a schema of representation of various components and system prototype to check the compliance before accepting second appeal. The schema was created using subset of AKOMA-NTOSO schema, XML & HTML standard. The result shows that quality of services are improved by eighty percent(80%) and it has the potential to augment the way to create schema for entire RTI ACT. There are challenges associated with complexities in judicial system and quality of encoding of law on the basis of schema created and development of system to act accordingly. The study provided evidence that data on law can be interchanged among various system with semantic and technical interpretability.
Kamalpreet Bindra and Anuranjan Mishra
IEEE
clustering in data mining is a supreme step towards organizing data into some meaningful patterns. It plays an extremely crucial role in the entire KDD process also as categorizing data is one of the most rudimentary steps in knowledge discovery. Clustering is used for creating partitions or clusters of similar objects. It is an unsupervised learning task used for exploratory data analysis to find some unrevealed patterns which are present in data but cannot be categorized clearly. Sets of data can be designated or grouped together based on some common characteristics and termed clusters, the implementation steps involved in cluster analysis are essentially dependent upon the primary task of keeping objects with in a cluster more closer than objects belonging to other groups or clusters. Depending on the data and expected cluster characteristics there are different types of clustering algorithms. In the very recent times many new algorithms have emerged which aim towards bridging the different approaches towards clustering and merging different clustering algorithms given the requirement of handling sequential, high dimensional data with multiple relationships in many applications across a broad spectrum. The paper aims to survey, study, and analyze few clustering algorithms and provides a comprehensive comparison of their efficiency on some common grounds.
Amba Mishra, Prashant Johri, and Anuranjan Mishra
IEEE
As information sharing over the internet has been increased has raised the problem of security of digital data on the device as well as the communication channel through which the information is shared. Many techniques have been used so far to secure the valuable data and steganography is one of them. It is a technique used to conceal the secret data within a normal appearing cover media i.e. it makes the secret message almost invisible for any unwanted recipient. To make our steganography algorithm more secure, here we are encoding the secret data into its ASCII and then GA is Applied to the audio samples of cover file in order to get an optimum position to hide the data, after this LSB is used to embed the ASCII codes of the secret data.
RECENT SCHOLAR PUBLICATIONS
Publications
Papers in International Journals
1. Madan Mohan, Aadarsh Malviya, Anuranjan Mishra “Big Data Security Problem and Its Solutions ” International Journal of Engineering and Advanced Technology (IJEAT) ISSN: 2249-8958 (Online), Volume-11 Issue-1, October 2021, DOI: 10.35940/
2. Madan Mohan, Aadarsh Malviya, Anuranjan Mishra “Importance of Security in Big Data Log Files on Cloud” International Journal of Engineering and Advanced Technology (IJEAT) ISSN: 2249-8958 (Online), Volume-11 Issue-1, October 2021, DOI: 10.35940/
3. Shashi Shashi , Suryakant Yadav, Anuranjan Mishra “A Prototype for Data Integrity in Cloud Environment” EAI Endorsed Transactions on Cloud Systems June- September 2020, Volume 6 | Issue 18 | e7,PP 1-5.ISSN: 2410-6895, DOI: 10.4108/
4. Dr Anuranjan Misra, Kaushiki kumara "Blockchain Enabled E-Voting System" in Dogo Rangsang Research Journal UGC Care Group I Journal ISSN : 2347-7180 Vol-10 Issue-08 No. 11 August 2020.
5. Ms Divya Misra, Dr. Anuranjan Misra, “Performance Enhanced and Improvised Approach to Reduce Call Drops Using LTE-SON”,“ Computational Network Application Tools for Performance Management”,PP 153-166 ,Springer Singapore Pte Ltd. 2020, ISBN 978-981-32-9584-1 ISBN 978-981-32-9585-8 (eBook),
6. Dr Anuranjan Misra, Suyash Mishra, Dr Suryakant yadav " Improving Map ReducePerformance using LATE scheduling in big data", in Journal of Emerging Techno
GRANT DETAILS
• Rs 50,000 Under Unnat Bharat Abhiyan by Ministry of Education, Government of India.
• Rs 2 Lacs approved under Mission Amrit Sarovar - Jal Dharohar Sanrakshan by Ministry of Housing & Urban Affairs and implemented by AICTE.
• Rs 1 Crore Approved for GNIOT- MSME Incubation Center by Ministry of MSME, Government of India
• Rs 15 Lakhs Approved Under Unnat Bharat Abhiyan for 15 Village centric Projects by Ministry of Education, Government of India.
• Rs 1 Lac approved under AICTE- Scheme for Promoting Interests, Creativity and Ethics among Students (SPICES)
RESEARCH OUTPUTS (PATENTS, SOFTWARE, PUBLICATIONS, PRODUCTS)
1. International Patent published on “SOLAR PV POWER INTEGRATED SMART GRID BASED ENERGY MANAGEMENT SYSTEM” with 3 claims & 16 Pages, ID= 2021101174 A, in the Volume/Issue : 35/12 dated 25-03-2021 and Patented Patent number: 2021101174 granted on 21 April 2021 by Australian Government.
2. National Patent published on “IOT Based Smart Home Security System” with 3 claims & 16 Pages, ID= 202121010183 A, in the Patent office Journal dated 19-03-2021.
3. National Patent published on “ARTIFICIAL INTELLIGENCE BASED INTERNET-OF-VEHICLES (IOV) SYSTEM TO PREVENT ROAD ACCIDENTS” with 3 claims & 16 Pages, ID= 202141011709 A, in the Patent office Journal dated 26-03-2021.
4. National Patent published on “ARTIFICIAL INTELLIGENCE BASED SYSTEM FOR FACE DETECTION AND IDENTIFICATION OF MASKED FACES DURING COVID PANDEMICS” with 3 claims & 16 Pages, ID= 202141015648 A, in the Patent office Journal dated 16-04-2021.
5. National Patent published on “WEARABLE DEVICE FOR SENSING AND PREDICTING UNEXPECTED ACCIDENTAL LIFE SITUATIONS USING MOBILE CROWD SENSING” with 10 claims & 31 Pages, ID= 202141017166 A, in the Patent office Journal dated 23-04-2021.
6. National Patent published on “IDENTIFICATION OF PLANT LEAF DISEASE PREDICTION USING MACHINE LEARNING ALGORITHMS” with 06 claims & 20 Pages, ID= 202141041021 A, in the Patent office Journal dated 24-09-2021.