MANDAR KRISHNARAO MOKASHI
@viit.ac.in
Assistant Professor, Department of Information Technology
Vishwakarma Institute of Information Technology, Pune
RESEARCH INTERESTS
Wireless Sensor Network
Scopus Publications
Scopus Publications
Valarmathy AS, Mandar K. Mokashi, Sunil Kumar Jakhar, Vaishali Singh, Asha KS, and Ashmeet Kaur
IEEE
The integration of artificial intelligence (AI) with records science can result in extra efficient and accurate outcomes in the evaluation of large datasets. AI techniques have already been validated to be helpful to facts and technological know-how via automating certain information preprocessing, function engineering, version training, and parameter tuning tasks. In this paper, we discuss the automation process for data analysis, which involves the use of AI techniques such as machine learning, natural language processing, and predictive modeling to automate the data analysis process. This not only saves time and resources but also eliminates the potential for human errors. We also highlight the benefits of this approach, including improved accuracy, efficiency, and scalability. Furthermore, we explore the role of data scientists in this automation process and how they can work together with AI to achieve the best results from data science. Finally, we discuss some potential challenges and limitations of automation in data analysis and suggest ways to overcome them. By harnessing AI to automate the data analysis process, organizations can tap into the full potential of their data and make informed decisions that drive business growth and success. By using AI, information scientists can gain entry to the kingdom of the art strategies to progress further in their data science journey.
Asha Sohal, Sandeep Sharma, Sweta Agarwal, N. V. Balaji, D. Bhanu, and Mandar Krishnarao Mokashi
IEEE
Current wireless communications use the microwave band as its medium. Present-day wireless network makes use of the majority of the available spectrum. The word innovative Full-Duplex (FD) as well as the use Getting NOMA sharing scheme called Reflecting In-Band Full-Duplex (R-IBFD) is suggested in which piece in order to advance technology and meet the requirements of better utilizing these natural assets. In order to meet the needs of smart cities for 6th Generations (6thG or 6G), the suggested R-IBFD offers efsfective use of airwaves with superior system characteristics, including Concealment Outage Potential (SOP), efficiency, communication percentage, and secrets capacity. The suggested method aims to address the need for innovative algorithms which foster better transformation and usher with a digital shift in business specifications for 6G. Addressing suggested R-IBFD within this research primarily responds to the phenomenon of interference between channels related security issues. Most interference from co-channels experienced by In-Band Full-Duplex type devices experience among their individual communicating and reception antennas is greater. The use of R-IBFD lessens the impact of this disturbance and helps to secure a necessary transmission infrastructure. Using the aid of SOP creation, formulas, and modeling outcome, simulation, the rise of concealment capability and interaction using R-IBFD are explored for an improved comprehension of its contributions. Among of the many evaluation technologies being utilized to increase the concealing capabilities is an artificial algorithm based on genes.
Harshada P. Bhambure and Mandar Mokashi
IEEE
The user enters any query to find desired information. To discover number of user search goals and representing each goal with some keyword, we first infer user search goals for a query by clustering feedback sessions. For that, we use a concept of pseudo document, which is the revised version of feedback session. Then the user search goals are determined by clustering the pseudo documents and it also represents the cluster with some keyword. Evaluation is done by using the Classified Average Precision (CAP), it is used to evaluate the performance of the restructured web search results. The existing system is using the k means clustering algorithm but in proposed system, we are using bisecting k means clustering algorithm which is increasing the efficiency of result. After the segmented result formation, the result in the every segment is reorganized as per number of clicks of URLs. The link which is clicked more number of times will appear at first location in the segment. This reduces the time requirement for searching.
Sagar Sudhakar Mane and M.K. Mokashi
IEEE
In this paper, we present Real-Time Flash-Flood Monitoring, Alerting and Forecasting System using Data mining and wireless sensor Network. Our System not only Measures River Water level and Different weather conditions such as temperature, humidity and vibration through wireless sensor nodes but also we can forecast possibility of future disasters by using Data mining algorithm on our database.
Harshada Bhambure and Mandar Mokashi
IEEE
The goal of the user at the time of searching the data is unknown to the system. The important aspect of searching process is to first recognize the user goal. On the basis of the recognized goal results are shown to the user. The goal identification requirement can be fulfilled by using pseudo document and feedback session. Click through logs are used to create feedback session. Pseudo document is the revised version of feedback session for clustering the websites. This paper reviews many web mining techniques for inferring the user goals. Query suggestion techniques are examined in this. It also studies the comparison of list and category methods of search result which helps to select the best method.