Tripura Institute of Technology

About: Tripura Institute of Technology is a based out in . It is known for research contribution in the topics: Electric power system & Renewable energy. The organization has 63 authors who have published 92 publications receiving 510 citations.

Gauss-Seidel Method based Voltage Security Analysis of Distribution System

Abstract: Complexity of modern power network and Large disturbance results voltage collapse. So, voltage security analysis is important in power system. Indicators are helpful in voltage stability analysis, as they give information about the state of the system. In this paper a new indicator namely Distribution System Stability Indicator (DSSI) has been formulated using the information of Phasor Measurement Unit (PMU).The proposed indicator (DSSI) is tested on standard IEEE 33 bus radial distribution system. The suggested indicator is also applicable to the equivalent two bus system of a multi-bus power system. The proposed indicator is calculated for different contingent conditions at different system load configurations. The result of DSSI is verified with the standard indicator (VSI) which proves applicability of the proposed indicator. The bus voltages of all the buses at base loading and at maximum loading are evaluated for base data and for tripping of most critical line.

A DVR-Based Routing Protocol with Special Neighbours for Mobile Ad-Hoc Networks

Abstract: We develop a Modified DVRA (MDVRA), distance vector protocol for mobile ad-hoc network. Our objective was primarily intended to remove the weaknesses inherent in the widely used DVRA, based on the well-known Bellman-Ford shortest path algorithm. Additionally, the goal was also to enhance the capabilities of the DVRA as to make it an efficient, robust and fully dynamic practical routing algorithm which may prove itself attractive enough for being used more extensively in general network as well as in the global Internet. As a distributed dynamic routing algorithm which is expected to adapt to changes in topology and traffic, the existing DVRA suffers mainly from two types of problems, namely, the problem of slow convergence with occasional count-to-infinity (CTI) and, occasional route oscillations. This paper, proposed routing protocol that use to create the MDVRA that would be truly dynamic, robust and free from the various limitations that have been discussed.

Detection of Early Breast Cancer Using A-Priori Rule Mining and Machine Learning Approaches

Abstract: In today’s world, breast cancer is extremely predominant in females that establishes in the breast and further extends to other locales of the body in the track of time. It is the second major ailment that causes decease. In long term, an early detection can reduce the death rate due to breast cancer appreciably. The crucial point for early prediction is to recognize the cancer cells at virgin stages. Various researches are carried out on breast cancer detection using mammography, ultrasounds, CT scans, PET, MRI, biopsy, etc. Still, these techniques are expensive, prolonged and sometimes unsuitable for young females. Hence, a fast and accurate detection system is highly demanded. In recent years, data mining and machine learning techniques are given utmost attention for early stage breast cancer detection. The aim of this paper is to present a framework for accurate and quick conclusion of breast cancer using machine learning techniques. We applied our proposed technique on SEER dataset of breast cancer and obtained highly appreciable results with accuracy of 99.9% using random forest. Various rules are also presented in support of breast cancer detection using A-priori algorithm.

Period Formula for Reinforced Concrete Buildings with Infill Walls

Abstract: The calculation of fundamental time period of vibration is a crucial step in seismic design and analysis of the structures to assess global response of the structure. Different international code proposed empirical expressions considering only height for bare frame structures and height and width of the buildings with infill to estimate the fundamental time period. This paper summaries the effect of the following parameters of building height, bay width, number of bays, cracked or un-cracked section of the structural member and support condition at the base on the fundamental time period of reinforced concrete bare frame and buildings with infill. Modal analysis of 360 building models with selected parameters is investigated in this study. A new equation, which is a function of the selected parameters (building height, bay width, number of bays, type of support condition, cracked or un-cracked sections and type of frame chosen for analysis) is also proposed using multiple linear regression analysis for predicting the fundamental period of buildings. The proposed simple model, including the building height, bay width, number of bays, type of support condition, cracked or un-cracked sections and type of frame chosen for analysis, showed better estimate in predicting the fundamental period of buildings compared to the code equations.