National Institute of Technology, Meghalaya

About: National Institute of Technology, Meghalaya is a education organization based out in Shillong, India. It is known for research contribution in the topics: Control theory & Electric power system. The organization has 503 authors who have published 1062 publications receiving 6818 citations. The organization is also known as: NIT Meghalaya & NITM.

Development of a PID Control Strategy for a Compact Autonomous Underwater Vehicle

Abstract: This paper presents a proportional-integral-derivative (PID) control strategy for navigation of a compact autonomous underwater vehicle (AUV) developed in-house. The AUV has a closed frame, neutrally buoyant, three-part modular structure made up of glass fibre composite material. Three fix position bi-directional thrusters are used for propulsion. A detailed CAD model of the AUV is developed using the modelling software SOLIDWORKS to estimate different system parameters. Hydrodynamic parameters are estimated from the ANSYS Fluent simulations of the AUV structure. Using the system parameters, a six degrees of freedom (DOF) dynamic model is developed, which is further simplified to a 4 DOF model. A 3D guidance system is developed for path planning using Line-of-Sight (LOS) strategy with way-point navigation. A closed loop PID controller is developed to follow the trajectory developed by the guidance system. The controller is simulated using MATLAB Simulink and the results are discussed.

Experimental and DFT generated Raman study of two bent-core monomeric liquid crystalline compounds

Abstract: The temperature dependence Raman spectra of two liquid crystalline compounds defined by the chemical formula of 3,5-difluoro-4ʹ-(4-pentylcyclohexyl)-(1,1ʹ-biphenyl)-4-carbonitrile and 3,4,5-trifluo...

Integrative Analysis of Multi-Genomic Data for Kidney Renal Cell Carcinoma

Abstract: Accounting for nine out of ten kidney cancers, kidney renal cell carcinoma (KIRC) is by far the most common type of kidney cancer. In view of limited and ineffective available therapies, understanding the genetic basis of disease becomes important for better diagnosis and treatment. The present studies are based on a single type of genomic data. These studies do not consider interactions between genomic data types and their underlying biological relationships in the disease. However, the current availability of multiple genomic data and the possibility of combining it have facilitated a better understanding of the cancer’s characterization. But high dimensionality and the existence of complex interactions (within and between genomic data types) are the two main challenges of integrative methods to analyze cancer effectively. In this paper, we propose a method to build an integrative model based on Bayesian model averaging procedure for improved prediction of clinical outcome in cancer survival. The proposed method initially uses dimensionality reduction techniques to generate low-dimensional latent features for the predictive models and then incorporates interactions between them. It defines the latent features using principal components and their sparse version. It compares the predictive performance of models based on these two latent features on real data. These models also validate several ccRCC-specific cancer biomarkers previously reported in the literature. Applied on kidney renal cell carcinoma (KIRC) dataset of The Cancer Genome Atlas (TCGA), the method achieves better prediction with sparse principal components model by including latent feature interactions as compared to without including them.

Dynamic Modelling and Control of a Compact Autonomous Underwater Vehicle

Abstract: This paper presents the dynamic modelling and control of a developed compact autonomous underwater vehicle (AUV), which has a closed frame, neutrally buoyant, a three-part modular structure made up of glass fibre composite material. The robot uses three fix position bi-directional thrusters for propulsion, out of which two thrusters are used for horizontal planar motion and the third one is used for vertical motion. A detailed 3D model of the AUV has been developed using the CAD modelling software SOLIDWORKS to determine the system parameters. Kinematic analysis has been carried out to correlate the local and global position, velocity and acceleration of the AUV. Computational fluid dynamics (CFD) software ANSYS Fluent is used for boundary layer study to determine the hydrodynamic parameters. Using the kinematic and hydrodynamic parameters a six degrees of freedom (DOF) dynamic model is developed. With appropriate assumptions, the complex 6 DOF coupled non-linear dynamic model is simplified to a 4 DOF model. A closed-loop PD controller is developed using the partitioning law and the system dynamic model, which is simulated using MATLAB Simulink. A 3D guidance system is developed to follow path generated by waypoint technique using Line-of-Sight (LOS) strategy. This work will find application in the navigation of the AUV in a predefined path.