IRJCS Published Papers by Pallavi Gupta (SUSET Associate Professor)
IRJCS: International Research Journal of Computer Science, 2020
Reinforcement learning (RL) is a subfield of machine learning which is being developed in Artific... more Reinforcement learning (RL) is a subfield of machine learning which is being developed in Artificial Intelligence (AI). This technique is a data independent process. The primary aim of systems this kind is to maximize their reward signal which makes systems do better things trending to goal. Reinforcement Learning alters with techniques like supervised and unsupervised in such a way that in RL the agent gets up with its own insights and maps what action to perform in certain situations. On the other hand, Supervised and unsupervised have answers already embedded in them. In RL, in absence of new data, it can learn from its own experience where others can do. RL is used almost everywhere, the best applications of RL in Robotics specifically in motion control, planning it is also used in finance, gaming etc. Here is this paper demonstrating the navigation and motion control development of a 2 wheeled differential drive robot with the help of reinforcement learning topology. Traditionally, to design the behaviour of controllers in robots, we inevitably need models of how the robot actually behaves in the environment. But here we come up with a RL approach to design the control structure for the robot to navigate in the indoor environment.
Papers by Pallavi Gupta (SUSET Associate Professor)
This paper proposes a novel design approach for a secured compressed sensing system for fingerpri... more This paper proposes a novel design approach for a secured compressed sensing system for fingerprint imaging and its transmission. In the proposed design, the first stage is acquiring the signal followed by sparsely modeling it using Orthogonal Matching Pursuit (OMP) algorithm. In addition to compressing, to guaranty its security, we multiply the sparse modeled data by a novel deterministic partially orthogonal Discrete Cosine Transform (DCT) sensing matrix. Furthermore, the construction of the sensing matrix uses a modified Multiplicative Linear Congruential Generator (MLCG) to select the row index appropriately from chaotically re-arranged rows of DCT pseudo-randomly. On the other hand, the simultaneous recovering and decryption of the compressed image accomplished with the help of a convex optimization method. The proposed system tested by employing different image and security assessment techniques. The results show that we have archived better Peak Signal to Noise Ratio (PSNR) t...
Current discovery of the memristor has sparked a new wave of enthusiasm and optimism that has res... more Current discovery of the memristor has sparked a new wave of enthusiasm and optimism that has resulted in revolutionizing circuit design. Memristive devices are potential elements for nanoelectronics applicable in nonvolatile memory and storage, defect-tolerant circuitry and neuromorphic computing. We present its main applications in the circuit design and computer technology, together with future developments.
Multimedia Tools and Applications
A novel deterministic sensing matrix design approach applied to enable secured compressed sensing... more A novel deterministic sensing matrix design approach applied to enable secured compressed sensing and transmission of fingerprint images. The performance of the sensing matrix was analyzed in detail by varying compressed sensing and security parameters. The number of sampling and sparse coefficient are the parameters taken under consideration from compressed sensing, whereas the encryption key is from the security scheme. The first stage in the performance study is acquiring the signal, and followed by sparsely modelling it using Orthogonal Matching Pursuit (OMP) algorithm. The sparse modelled data is multiplied by the proposed deterministic partial orthogonal Discrete Cosine Transform (DCT) sensing matrix to reduce its dimension and encrypt it. To introduce confusion on the DCT matrix rows, the pseudorandom permutation is applied to the DCT matrix rows before sensing matrix derivation. Additionally, recovering and decryption of the compressed image accomplished with the help of a convex optimization method. The results obtained from the simulation of the proposed system confirmed that a better Peak Signal to Noise Ratio (PSNR) than the recommended value for wireless transmission is archived using a sample below 25% without losing a significant number of fingerprint minutiae.
2021 International Conference on Communication, Control and Information Sciences (ICCISc)
Piezoelectric MEMS (Micro-Electro-Mechanical Systems) are used in many applications now a day's i... more Piezoelectric MEMS (Micro-Electro-Mechanical Systems) are used in many applications now a day's including the diagnosis of diseases.COVID-19 is a pandemic recently affecting the entire world. Various techniques for detection are being used to date. Paper presents a simulation-based piezoelectric MEMS detection method for the virus, which is fast, portable, cost-effective, require less amount of sample, reliable, and can diagnose the stage for SARS-CoV-2(Severe acute respiratory syndrome corona virus 2) from the first day of virus infection. The design and analysis of cantilever-based MEMS biosensor is done COMSOL Multiphysics. Three cantilevers are used in the design, one each for viral load, IgM, and IgG. The bio-molecular reaction on the cantilever increases the mass at the end, changing the electrical and mechanical properties in the cantilever. Piezoelectric material generates the voltage proportional to the mass applied. From the values of voltage obtained from three cantilevers, the infection stage for symptomatic and asymptomatic can be diagnosed. Results show a linear relationship between the load applied and voltage generated. The proposed biosensor has a mass sensitivity of 20 copies /ml.
International Journal of Engineering and Advanced Technology
In this paper, the effect of module discoloration on electrical parameters degradation was analyz... more In this paper, the effect of module discoloration on electrical parameters degradation was analyzed. The discoloration was initially identified through visual inspection method. The visual image shows that the module has changed color to brown, and there is no discoloration on the module metallization. Furthermore, the module discoloration was correlated with the electrical parameters degradation. The analysis shows that Isc and Pmax have degraded high. This indicates that discoloration defect has correlated well with Isc and Pmax degradation. The annual power degradation rate of module 1 and 2 are found to be 2.25/year and 1.56/year respectively.
International Research Journal of Computer Science
Reinforcement learning (RL) is a subfield of machine learning which is being developed in Artific... more Reinforcement learning (RL) is a subfield of machine learning which is being developed in Artificial Intelligence (AI). This technique is a data independent process. The primary aim of systems this kind is to maximize their reward signal which makes systems do better things trending to goal. Reinforcement Learning alters with techniques like supervised and unsupervised in such a way that in RL the agent gets up with its own insights and maps what action to perform in certain situations. On the other hand, Supervised and unsupervised have answers already embedded in them. In RL, in absence of new data, it can learn from its own experience where others can do. RL is used almost everywhere, the best applications of RL in Robotics specifically in motion control, planning it is also used in finance, gaming etc. Here is this paper demonstrating the navigation and motion control development of a 2 wheeled differential drive robot with the help of reinforcement learning topology. Traditionally, to design the behaviour of controllers in robots, we inevitably need models of how the robot actually behaves in the environment. But here we come up with a RL approach to design the control structure for the robot to navigate in the indoor environment.
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IRJCS Published Papers by Pallavi Gupta (SUSET Associate Professor)
Papers by Pallavi Gupta (SUSET Associate Professor)