Indian Institute of Technology Guwahati

About: Indian Institute of Technology Guwahati is a education organization based out in Guwahati, Assam, India. It is known for research contribution in the topics: Catalysis & Computer science. The organization has 6933 authors who have published 17102 publications receiving 257351 citations.

Detection of Shockable Ventricular Arrhythmia using Variational Mode Decomposition

Abstract: Ventricular tachycardia (VT) and ventricular fibrillation (VF) are shockable ventricular cardiac ailments. Detection of VT/VF is one of the important step in both automated external defibrillator (AED) and implantable cardioverter defibrillator (ICD) therapy. In this paper, we propose a new method for detection and classification of shockable ventricular arrhythmia (VT/VF) and non-shockable ventricular arrhythmia (normal sinus rhythm, ventricular bigeminy, ventricular ectopic beats, and ventricular escape rhythm) episodes from Electrocardiogram (ECG) signal. The variational mode decomposition (VMD) is used to decompose the ECG signal into number of modes or sub-signals. The energy, the renyi entropy and the permutation entropy of first three modes are evaluated and these values are used as diagnostic features. The mutual information based feature scoring is employed to select optimal set of diagnostic features. The performance of the diagnostic features is evaluated using random forest (RF) classifier. Experimental results reveal that, the feature subset derived from mutual information based scoring and the RF classifier produces accuracy, sensitivity and specificity values of 97.23 %, 96.54 %, and 97.97 %, respectively. The proposed method is compared with some of the existing techniques for detection of shockable ventricular arrhythmia episodes from ECG.

Simultaneous removal of methylene blue and Pb2+ ions using ruthenium nanoparticle-loaded activated carbon: response surface methodology

Abstract: Ruthenium nanoparticles were synthesized in a green approach with high yield in the presence of ultrasound and then the product was loaded on activated carbon. Characterization was performed using different techniques such as SEM, XRD, and BET. The simultaneous removal of methylene blue (MB) and Pb2+ ions from aqueous solution by ruthenium nanoparticles loaded on activated carbon (Ru-NPs–AC) was studied. The effects of variables such as initial dye and Pb2+ ion concentrations (mg L−1), adsorbent doses (g) and contact time (min) on the simultaneous removal of MB and Pb2+ ions were studied. Experiments were conducted using central composite design (CCD) and the optimum experimental conditions were found under response surface methodology (RSM). Adsorption equilibrium data were well fitted by the Langmuir isotherm model compared to the Freundlich, Temkin and Dubinin–Radushkevich models. Experimental adsorption data were analyzed using various kinetic models such as pseudo-first and second order, Elovich and intraparticle diffusion models. A good fit to the pseudo-second order model was observed. Dye removal varied from 77% to 99% within the operating conditions considered herein.

Water quality assessment of an untreated effluent impacted urban stream: the Bharalu tributary of the Brahmaputra River, India.

Abstract: Guwahati, the lone city on the bank of the entire midstream of the Brahmaputra River, is facing acute civic problem due to severe depletion of water quality of its natural water bodies. This work is an attempt towards water quality assessment of a relatively small tributary of the Brahmaputra called the Bharalu River flowing through the city that has been transformed today into a city drainage channel. By analyzing the key physical, chemical and biological parameters for samples drawn from different locations, an assessment of the dissolved load and pollution levels at different segments in the river was made. Locations where the contaminants exceeded the permissible limits during different seasons were identified by examining spatial and temporal variations. A GIS developed for the watershed with four layers of data was used for evaluating the influence of catchment land use characteristics. BOD, DO and total phosphorus were found to be the sensitive parameters that adversely affected the water quality of Bharalu. Relationship among different parameters revealed that the causes and sources of water quality degradation in the study area were due to catchments input, anthropogenic activities and poor waste management. Elevated levels of total phosphorus, BOD and depleted DO level in the downstream were used to develop an ANN model by taking total phosphorus and BOD as inputs and dissolved oxygen as output, which indicated that an ANN based predictive tool can be utilized for monitoring water quality in the future.