Akhilesh Pandey
@uudoon.in
Asst Professor
Uttaranchal University
RESEARCH, TEACHING, or OTHER INTERESTS
Computer Engineering, Computer Vision and Pattern Recognition
Scopus Publications
Scholar Citations
Scholar h-index
Scholar i10-index
Scopus Publications
Divya Rawat, Divya Rawat, Amaarjeet Rawat, Akhilesh Pandey, Gautam Chauhan, and Srinivas Aluvala
IEEE
This research article explores the legal and ethical challenges posed by artificial intelligence (AI). The authors examine the current state of AI regulations and highlight the need for clear ethical guidelines for its deployment. The article evaluates the potential for AI to infringe upon privacy rights and raises questions about the accountability of AI systems for their actions. It also discusses the role of international organizations in establishing ethical standards for AI. The authors argue that the development and deployment of AI must be guided by ethical principles, such as transparency, fairness, and accountability. They emphasize the need for a balanced approach that balances the benefits of AI with the need to protect human rights and dignity. The paper suggests that the establishment of ethical guidelines for AI will require the cooperation of governments, industry, and civil society. In conclusion, this research article provides an overview of the legal and ethical challenges posed by AI and highlights the need for clear guidelines for its responsible use. The authors suggest that international organizations should play a role in establishing ethical standards for AI deployment and emphasize the importance of continued research and debate on this important issue.
Akhilesh Pandey, Sameer Dev Sharma, Ankita Rawat, Divya Dalakoti, and Gotte Ranjith Kumar
IEEE
Climate change, biodiversity loss, soil degradation, water scarcity, and food insecurity are just a few of the issues threatening India's food system's sustainability. We require a more sustainable approach to food production and consumption in order to address these issues. We can influence lasting change in the food system by using the method to problem-solving known as "design thinking." This research paper aims to explore how design thinking can be used to design a better food system in India. We conducted a literature review of relevant studies, reports, and case studies and analyzed the findings to identify common themes and best practices. Our analysis revealed that design thinking can be used to design a better food system in India in several ways, including user-entered design, cross-sector collaboration, innovation and experimentation, and systems thinking. We present a case study of a design thinking approach to addressing food waste in India and discuss the implications and potential of design thinking for designing a better food system in India.
Ch.M. Shruthi, Vemullapalli Ramachandra Anirudh, Palla Bhargava Rao, Birru Shiva Shankar, and Akhilesh Pandey
EDP Sciences
Image deblurring is a challenging task that aims to restore a sharp and clear image from a blurred one. This problem is usually caused by camera motion or defocus blur. The objective of this paper is to develop a model that can effectively remove Gaussian blur from an image and improve its quality using deep learning techniques. Automated image deblurring is achieved using deep learning, this approach involves implementing a combination of convolutional neural networks (CNN) and simple auto encoders to train the model on a dataset of blurred and corresponding sharp images. The model is then used to deblur the test images and improve their quality. The paper uses a dataset of blurred and corresponding sharp images to train the model, and the performance of the model is evaluated based on metrics such as PSNR and SSIM. The results and discussions focus on the effectiveness of the model in removing Gaussian blur and improving the quality of the images. In conclusion, the paper demonstrates the effectiveness of using deep learning techniques for image deblurring and provides scope for future enhancements such as incorporating more complex models and exploring other types of blur removal techniques.
Venkataiah C., Mallikarjuna Rao Y., Manjula Jayamma, Linga Murthy M.K., Mahesh Kumar M., Laith H. Alzubaidi, and Akhilesh Pandey
EDP Sciences
This work presents comparison of ternary combinational digital circuits that reduce energy consumption in low-power VLSI (Very Large Scale Integration) design. CNTFET and GNRFET-based ternary half adder (THA) and multiplier (TMUL) circuits has been designed using ternary unary operator circuits at 32nm technology node and implement two power supplies Vdd and Vdd/2 without using any ternary decoders, basic logic gates, or encoders to minimize the number of used transistors and improve the energy efficiency. The effect of CNTFET and GNRFET parametric variation with threshold voltage on performance metrics namely delay and power has been analyzed. Dependence of threshold voltage on the geometry of carbon nanotube and graphene nanoribbon makes it feasible to be used for ternary logic design. It is analyzed that CNTFET based circuits are energy efficient than the GNRFET- based circuits. It is also concluded that the CNTFET-based circuitshas less power-delay product (PDP) when compared to GNRFET- based circuits. CNTFET-based THA is 23.5% more efficient than GNRFET-based THA and CNTFET-based Tmul is97.8% more efficient than GNRFET-based Tmul.All the digital circuits have been simulated using HSPICE tool.
Chiranjit Dutta, M Maheswari, K G Saravanan, Navdeep Dhaliwal, Akhilesh Pandey, and S Sophia
IEEE
The Cyber Physical System (CPS) is referred as the amalgamation of physical system with control system mechanisms. CPS is largely used in versatile process from automation, controlling and monitoring process. This is the process of converting the physical system into a digital platform through sensing, data storage and monitoring process. Due to the advancement in the Internet of Things (IoT), the cyber security has become a complex parameter. Thus they need to be considered. To overcome the constraints, the machine learning is implemented to provide security concerns for the cyber physical systems. The machine learning provides a platform for the intrusion detection system. The machine learning helps in the classification and detection of the cyber-attacks. This is done through the optimization techniques, which helps to provide the solution for reducing the complexity. The internet of system paved way for the sensing, control, monitoring and communication of information. The attacks in the networking system are identified through the machine learning that enable smart applications in diverse fields.
Shivani Saini, Sharvan Kumar Garg, Pankaj Pratap Singh, Arif Ali, and Akhilesh Pandey
Springer Nature Switzerland
Aakrati Nigam, Avdhesh Kumar Tiwari, and Akhilesh Pandey
Elsevier BV