Browsing by Author "Kumar, V.S."

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Enhanced Last-Touch Interaction Attribution Model in Online Advertising
(2019) Yuvaraj, C.B.; Chandavarkar, B.R.; Kumar, V.S.; Sandeep, B.S.
The increased popularity of an internet opened a new way for e-business in terms of digital advertisement. In order to get back and improve the "return of investment", how to allocate the revenue distribution to different marketing channels comes out to be the key problem in digital advertising. However, last interaction model, first interaction model, last click, last ad words' click, linear attribution, time-decay attribution, position based attribution models are some of the attribution models developed to attribute and assign contribution to each marketing channel. These existing models consider the contributions of the other channels and some don't consider the synergistic effects in revenue calculation from different marketing channels. This paper proposes Enhanced Last Touch Interaction (ELTI) model to allocate the revenue distribution to different marketing channels using game theory and synergistic effects. Additionally, the paper also implements and adopts the probabilistic approaches to prevent the simple intuitions made by many other attribution models. Prediction accuracy of above 75% of the ELTI model out performance the state-of-the art models. � 2018 IEEE.
Enhanced Last-Touch Interaction Attribution Model in Online Advertising
(Institute of Electrical and Electronics Engineers Inc., 2018) Yuvaraj, C.B.; Chandavarkar, B.R.; Kumar, V.S.; Sandeep, B.S.
The increased popularity of an internet opened a new way for e-business in terms of digital advertisement. In order to get back and improve the "return of investment", how to allocate the revenue distribution to different marketing channels comes out to be the key problem in digital advertising. However, last interaction model, first interaction model, last click, last ad words' click, linear attribution, time-decay attribution, position based attribution models are some of the attribution models developed to attribute and assign contribution to each marketing channel. These existing models consider the contributions of the other channels and some don't consider the synergistic effects in revenue calculation from different marketing channels. This paper proposes Enhanced Last Touch Interaction (ELTI) model to allocate the revenue distribution to different marketing channels using game theory and synergistic effects. Additionally, the paper also implements and adopts the probabilistic approaches to prevent the simple intuitions made by many other attribution models. Prediction accuracy of above 75% of the ELTI model out performance the state-of-the art models. Â© 2018 IEEE.
PMSChain: A Blockchain-based Prison Management System using the Ethereum Platform
(Institute of Electrical and Electronics Engineers Inc., 2025) Niha, N.K.; Janani, T.; Kumar, V.S.; Shrivas, M.
The prison system in India lags other industries, such as healthcare, in terms of automation. The existing prison management system often lacks transparency, consistency in security information, and well-defined procedures. To address this issue, we developed a system to digitize daily prison operations. The proposed blockchain-based prison management system is a comprehensive software application designed to manage activities related to prisons using a distributed ledger for efficient storage and managing information related to lawbreakers. The prison authority can have access to add, delete, or update the lawbreaker data that is collected from the police. The suggested system defines various roles for accessing the data inside the prison. Proper and timely access to data is enabled for the prison authorities. The proposed system has been implemented using the Ethereum Sepolia test net with 1000 tractions and its total transaction cost is 0.015357. Additionally, gas price, throughput, and latency has been computed for the proposed work. This system has been designed to provide secure, efficient, and user-friendly management of inmate records, scheduling, and communication. This system enables tamper-proofness, accountability and security of data by incorporating blockchain technology for secure and immutable record transaction within prison which prevents fraud, and corruption. Â© 2025 IEEE.
Wearable sensor-based human fall detection wireless system
(2019) Kumar, V.S.; Acharya, K.G.; Sandeep, B.; Jayavignesh, T.; Chaturvedi, A.
Background/Objectives: Human fall detection is a critical challenge in the healthcare domain since the late medical salvage will even lead to death situations, therefore it requires timely rescue. This research work proposes a system which uses a wearable device that senses human fall and wirelessly raises alerts. Methods/statistical analysis: The detection system consists of the sensor system which contains both accelerometer and gyroscope sensors. The proper orientation of the subject is provided by the Madgwick filter. Six volunteers were engaged to perform the falling and non-falling events. The system is validated and checked by four algorithms: threshold based, support vector machine (SVM), K-nearest neighbor, and dynamic time wrapping, and thus, the accuracy was calculated. Findings: From the results obtained, the SVM has given an accuracy of 93%. Conclusions: When a fall is being detected, an additional feature to check whether the person is in critical state and is lying down for more than a particular time is incorporated and a critical alert is sent to the caretaker�s mobile. � Springer Nature Singapore Pte Ltd. 2019.
Wearable sensor-based human fall detection wireless system
(Springer Verlag service@springer.de, 2019) Kumar, V.S.; Acharya, K.G.; Bairampalli, B.; Thyagarajan, T.; Chaturvedi, A.
Background/Objectives: Human fall detection is a critical challenge in the healthcare domain since the late medical salvage will even lead to death situations, therefore it requires timely rescue. This research work proposes a system which uses a wearable device that senses human fall and wirelessly raises alerts. Methods/statistical analysis: The detection system consists of the sensor system which contains both accelerometer and gyroscope sensors. The proper orientation of the subject is provided by the Madgwick filter. Six volunteers were engaged to perform the falling and non-falling events. The system is validated and checked by four algorithms: threshold based, support vector machine (SVM), K-nearest neighbor, and dynamic time wrapping, and thus, the accuracy was calculated. Findings: From the results obtained, the SVM has given an accuracy of 93%. Conclusions: When a fall is being detected, an additional feature to check whether the person is in critical state and is lying down for more than a particular time is incorporated and a critical alert is sent to the caretakerâ€™s mobile. Â© Springer Nature Singapore Pte Ltd. 2019.