ECU Health Monitor Using CANUSB

Sutar, Abhijit D.; Shinde, Sagar

doi:10.1109/icicct.2018.8473000

Cited by 4 publications

(3 citation statements)

References 4 publications

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“…An onboard diagnostics system, also known as an OBD, helps the vehicle's electronic control unit (ECU) identify the malfunction of the vehicle systems and take immediate corrective measures to prevent the hazards and accidents. This type of system enhances the passenger and driver's safety (Sutar and Shinde 2018).…”

Section: Discussionmentioning

confidence: 99%

Advanced adaptive cruise control and vehicle to vehicle communication using LiDAR

Shinde,

Wadhwa,

Rawandale

et al. 2023

Multidiscip. Sci. J.

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The ACC system is a type of driving assistance that helps reduce the burden on a driver. It operates by controlling the vehicle's acceleration and deceleration to maintain a certain speed or avoid a collision. In order to improve the accuracy of its operation, this paper proposes a method that uses radar to detect the presence of the preceding vehicle. It also takes into account the vehicle sideslip angle and the distance between the two vehicles. The proposed method can help improve the driving stability. In addition, we are currently using the vehicle-to-vehicle communication technology in our system. This type of inter-vehicle communication is not widely used yet and is a new paradigm in the field of communication. One of the main advantages of this type of communication is that it doesn't rely on third-party networks such as cellular networks. Despite the various advantages of this technology, it still has a long way to go before it can be fully deployed. The increasing number of operators who are interested in this technology has led to the development of more effective and efficient V2V solutions. This paper aims to provide a comprehensive analysis of the various challenges and benefits of this type of communication. The paper also focuses on the various security issues that are associated with this technology. One of these is the potential interference. This issue can prevent the system from operating efficiently. In order to address this issue, the paper suggests an improved architectural solution that can help prevent this type of interference. The proposed work also proposes a standardized space for the various components of the V2V system. This will allow them to easily integrate into the system. Vehicle-to-Vehicle communication is a type of wireless communication that is designed to allow cars to talk to one another.

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Section: Discussionmentioning

confidence: 99%

Advanced adaptive cruise control and vehicle to vehicle communication using LiDAR

Shinde,

Wadhwa,

Rawandale

et al. 2023

Multidiscip. Sci. J.

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show abstract

“…The input scale of the SPEC2006 benchmark may be split into test, train, as well as reference scales; we utilize the reference scale to test." In this case, analysis was performed for multiple measures such as accuracy [22,23] and error metrics such as MSE, MSLE, and so on. In addition, IGHS outperformed the HGS, PRO, CMBO, ARCHOA, DO, as well as GOA models.…”

Section: A Simulation Setupmentioning

confidence: 99%

Compiler Optimization Prediction with New Self-Improved Optimization Model

Shewale¹,

Shinde²,

Gurav³

et al. 2023

IJACSA

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Users may now choose from a vast range of compiler optimizations. These optimizations interact in a variety of sophisticated ways with one another and with the source code. The order in which optimization steps are applied can have a considerable influence on the performance obtained. As a result, we created a revolutionary compiler optimization prediction model. Our model comprises three operational phases: model training, feature extraction, as well as model exploitation. The model training step includes initialization as well as the formation of candidate sample sets. The inputs were then sent to the feature extraction phase, which retrieved static, dynamic, and improved entropy features. These extracted features were then optimized by the feature exploitation phase, which employs an improved hunger games search algorithm to choose the best features. In this work, we used a Convolutional Neural Network to predict compiler optimization based on these selected characteristics, and the findings show that our innovative compiler optimization model surpasses previous approaches.

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“…The RMSE values with parameters for each benchmarks in the dataset is exposed in Table III. [25] is the key factor considered and it is achieved through derived features and neural network. The features like static and dynamic features as well as improved Relief based features were extracted.…”

Section: Study On Rmsementioning

confidence: 99%

A Novel Prediction Model for Compiler Optimization with Hybrid Meta-Heuristic Optimization Algorithm

Kadam¹,

Shinde²,

Gurav³

et al. 2022

IJACSA

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Compiler designer needs years or sometimes months to construct programs using heuristic optimization rules for a specified compiler. For every novel processor, the modelers require readjusting the heuristics to get the probable performances of processor. The most important purpose of the developed approach is to build a prediction approach with optimization constraints for transforming programs with a lesser training overhead. The problem has occurred in the optimization and it is needed to address it with novel prediction model with derived features & neural network. Here, a novel Compiler Optimization Prediction Model is developed. The features like static and dynamic features as well as improved Relief based features are derived, which are provided as input to Neural Network (NN) scheme, in which the weights are tuned via Honey Badger Adopted BES (HBA-BEO) model. Finally, the NN offers the final predicted output. The analysis outcomes prove the superiority of HBA-BEO model.

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ECU Health Monitor Using CANUSB

Cited by 4 publications

References 4 publications

Advanced adaptive cruise control and vehicle to vehicle communication using LiDAR

Advanced adaptive cruise control and vehicle to vehicle communication using LiDAR

Compiler Optimization Prediction with New Self-Improved Optimization Model

A Novel Prediction Model for Compiler Optimization with Hybrid Meta-Heuristic Optimization Algorithm

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