MAHESH AKARAPU

@sritw.org

ASSISTANT PRORESSOR AND COMPUTER SCIENCE AND ENGINEERING
SUMATHI REDDY INSTITUTE OF TECHNOLOGY FOR WOMEN

MAHESH AKARAPU


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https://researchid.co/maheshakarapu756

EDUCATION

M.TECH(CSE)

RESEARCH INTERESTS

ARTIFICIAL INTELLIGENCE AND MACHINE LEARNING
10

Scopus Publications

Scopus Publications

  • Automatic essay scoring using NLP
    M. Sheshikala, Mothe Rajesh, Mahesh Akarapu
    Aip Conference Proceedings, 2024
  • An artificial intelligence model estimating the typical energy usage for larger
    Mahesh Akarapu, Battu Chiranjeevi, Gadipe Sunitha, Masani Ruchinandan, M. Sheshikala, Rajasri Reddy
    Aip Conference Proceedings, 2024
  • Attendance system using RFID tag
    G. Mahesh Kumar, Eswaran Parthasarathy, Mahesh Akarapu, Ravichander Janapati
    Aip Conference Proceedings, 2022
  • Deep learning model for automatic image captioning
    Kothakonda Chandhar, C. H. Sandeep, Mahesh Akarapu, Kanegonda Ravi Chythanya, V. Thirupathi
    Aip Conference Proceedings, 2022
  • Safety in machine learning: Hazards, contradict actions, and assessments
    Mahesh Akarapu, Bonthala Prabhanjan Yadav, Kothakonda Chandhar, Koteshwar Rao Donthamala, K. Sreelatha
    Aip Conference Proceedings, 2022
  • Using the NI PXI platform for Li Fi-enabled intelligent transportation systems
    Y. Chanti, Mahesh Akarapu, B. Swathi, B. Vijaykumar, D. Kothandaraman
    Aip Conference Proceedings, 2022
  • An effective and strongly protecting information storage functions in mobile based cloud environment
    Mahesh Akarapu, Bonthala Prabhanjan Yadav, Y. Chanti, M. Shyamsunder, G. Krishna Priya
    Aip Conference Proceedings, 2022
  • Heterogeneous inter-Clue designing of POI Popularity Analysis with discrepancy Tourism Data
    Mahesh Akarapu, G. Sunil, Koteshwar Rao Donthamala, M Mrutyunjaya, D. Praveen
    Iop Conference Series Materials Science and Engineering, 2020
    The prevalence of Predicting Point of Interest (POI) has been extremely important to location-based applications, such as reviews on POIs. Many current approaches are rarely able to achieve adequate efficiency due to the shortage of POI knowledge. This tendentious restricts the advice to famous locations and lacks equally important qualities in unlikely attractions. This paper introduces a novel method to forecasting the performance of POIs, dubbed Hierarchical Multi-Clue Fusion (HMCF). In general, to address sparsity issues, it is proposed that POIs be defined in a simple way usage different method of User-Generated Content (UGC) By different origin. And there is construct a hierarchically powerful POI modeling framework that concurrently injects semantonal Awareness and multiple layer representation regulation of POIs. Users are building a multi-view POI database for assessment by compiling both text and visual information from four conventional tourism channels from many separate provinces in China during 2006 to 2017. Extensive experimental findings indicate that the new technique will substantially improve the output of forecasting the success of attractions relative to a variety of reference methodologies.
  • Checking for Identity-Based Remote Data Integrity Cloud Storage with Perfect Data Privacy
    Mahesh Akarapu, Sheshikala Martha, Koteshwar Rao Donthamala, B Prashanth, G. Sunil, K. Mahender
    Iop Conference Series Materials Science and Engineering, 2020
    Abstract The protection of the data maintained on a database system has the benefit that the cloud service creates a dynamic high-order and often a management issue comparable to the security operating costs. Multiple Online Compensation Monitoring Protocols have been developed to date that will pose a key problem to protect the privacy of cloud-based details. The much-needed role of the data servers is to render the data available to the consumer as necessary in the heavy traffic scenario. In this article, we planned privacy security for unavailable data held by the user, and promoted identification by using encryption strategies such as sha1 and sha2 algorithms to improve user data safety. We use zero general knowledge tests against third force Settlers which in effect improve the user data confidentiality. Under-reaching is achieved in our architecture by the use of file cabinet signature tune generating servers that operate in compliance with wirework traffic and attempt to access the less significant traffic wire work with the necessary details. Our strategy has proved to be safe in the face of threats of abuse, supplying the high-security department with identity-based consumer data deposit and improving efficiency by settling well on the server over cloud vehicle traffic. Implies being more directly linked to defensive shell, which often implies being protected which realistic.
  • Innovative teaching practice on "software engineering laboratory course
    A. Harshavardhan, D. Ramesh, P. Kumaraswamy, Mahesh Akarapu, Bhavana Jamalpur, YerrollaChanti
    Iop Conference Series Materials Science and Engineering, 2020
    Teaching Software engineering is very difficult because it includes theory and practical approach. Applying the theoretical knowledge is very complex. At the same time theory can’t be understood without applying. In this paper, we present an innovative teaching practice on the course “Software Engineering Practical” by which students will have a practical knowledge. We use different teaching steps and software tools to build an interactive lab atmosphere for the students to learn, recognize and understand the concepts of software engineering.