Anish Goyal
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Previous Organizations / Institutes
The organizations / institutes from the scholar's other articles in the past ten years
Research Subjects
Anish Goyal has a total of 10 co-authors. Here are the top co-authors by number of shared publications:
Antonio Sanchez-Rubio
MIT Lincoln Laboratory 3 , 244 Wood St., Lexington, Massachusetts 02420, USA
1 shared publication- Archit Bhatia
Netaji Subhas Institute of Technology, India
1 shared publication - Arjun Yadav
Netaji Subhas Institute of Technology, India
1 shared publication Burç Gökden
Harvard University School of Engineering and Applied Sciences 1 , 29 Oxford St., Cambridge, Massachusetts 02138, USA
1 shared publication- Christine S. Wang
Department of Pediatric Rheumatology C.S. Mott Children's Hospital and Michigan Medicine, University of Michigan Ann Arbor
1 shared publication - Deepak Kumar Sharma
Department of Information Technology, Indira Gandhi Delhi Technical University for Women, New Delhi, India
1 shared publication
Latest Publications
- Open Access
- 4 January 2023
- Published by Association for Computing Machinery (ACM)
- p. 431-437
Misbehavior Detection in Cooperative Intelligent Transportation Systems using Temporal Fusion Transformer
The United States in the early 20th century became the first nation to introduce the concept of intelligence in the transportation systems followed by intensive research and development by the European Countries like (Sweden, Switzerland), Japan, South Korea in the similar area. Since 1991, Intelligent Transport Systems (ITS) have been an emerging and promising area of research. This fact is also aided by the recent advancement and developments in the field of automated driving systems over the past few years. Cooperative Intelligent Transportation Systems (C-ITS) is the latest advancement over the existing Intelligent Transportation Systems (ITS) as now the systems are making use of communication and interaction with infrastructure using connected and automated vehicles (CAV’s) in order to create helpful and exciting applications that concern road safety, environment, mobility. Trust and Node Cooperation are the most crucial factors on which C-ITS relies as the decisions that are taken by a vehicle are based on the data and information it gets from the network infrastructure that is installed on the roadsides which is basically a pool of information which has been gathered from other vehicles and smart infrastructures that are part of the VANET. Presence of any misbehaviour in the network or a compromised node in the transport network system will lead to atrocious results for both traffic and network safety. Detecting any misbehaviour in the network can save us a lot of resources that will go into creating a system that can defend the complete network against a threat. Through the medium of our thesis project we will be detecting misbehaviour in the system using Deep Learning techniques. A most Basic MLP Neuron Architecture based Artificial Neural Network (ANN) would serve as our baseline and proposed models include LSTM and Transformer Model which will be used for time series classification.
- 4 January 2023
- Published by Association for Computing Machinery (ACM)
- p. 431-437
Open AccessMisbehavior Detection in Cooperative Intelligent Transportation Systems using Temporal Fusion Transformer
The United States in the early 20th century became the first nation to introduce the concept of intelligence in the transportation systems followed by intensive research and development by the European Countries like (Sweden, Switzerland), Japan, South Korea in the similar area. Since 1991, Intelligent Transport Systems (ITS) have been an emerging and promising area of research. This fact is also aided by the recent advancement and developments in the field of automated driving systems over the past few years. Cooperative Intelligent Transportation Systems (C-ITS) is the latest advancement over the existing Intelligent Transportation Systems (ITS) as now the systems are making use of communication and interaction with infrastructure using connected and automated vehicles (CAV’s) in order to create helpful and exciting applications that concern road safety, environment, mobility. Trust and Node Cooperation are the most crucial factors on which C-ITS relies as the decisions that are taken by a vehicle are based on the data and information it gets from the network infrastructure that is installed on the roadsides which is basically a pool of information which has been gathered from other vehicles and smart infrastructures that are part of the VANET. Presence of any misbehaviour in the network or a compromised node in the transport network system will lead to atrocious results for both traffic and network safety. Detecting any misbehaviour in the network can save us a lot of resources that will go into creating a system that can defend the complete network against a threat. Through the medium of our thesis project we will be detecting misbehaviour in the system using Deep Learning techniques. A most Basic MLP Neuron Architecture based Artificial Neural Network (ANN) would serve as our baseline and proposed models include LSTM and Transformer Model which will be used for time series classification.
- 4 February 2013
- Published by AIP Publishing in Applied Physics Letters
- Vol. 102 (5) , 053503
High-brightness tapered quantum cascade lasers
An index-guided tapered quantum cascade laser emitting near 9.5 μm with sloped sidewalls and no anti-reflection coating is presented, and the performance for devices with taper half-angles of 1° and 2° is investigated. The 1° device delivers up to 2.5 W of peak optical power at room temperature with beam quality-factor M2 = 2.08, while the two-degree device outputs 3.8 W with M2 = 2.25 for a maximum brightness of 1.87 MW cm−2 sr−1.
- 4 February 2013
- Published by AIP Publishing in Applied Physics Letters
- Vol. 102 (5) , 053503
High-brightness tapered quantum cascade lasers
An index-guided tapered quantum cascade laser emitting near 9.5 μm with sloped sidewalls and no anti-reflection coating is presented, and the performance for devices with taper half-angles of 1° and 2° is investigated. The 1° device delivers up to 2.5 W of peak optical power at room temperature with beam quality-factor M2 = 2.08, while the two-degree device outputs 3.8 W with M2 = 2.25 for a maximum brightness of 1.87 MW cm−2 sr−1.