Application of Entropy Techniques in Analyzing Heart Rate Variabilityusing ECG Signals

The variation of the heart rate about a mean value is the Heart Rate Variability (HRV). HRV reflects the functioning of cardio-respiratory control system. It is used as one of the diagnostic measures to detect heart disorders. In the proposed work, HRV analysis using entropy measures is carried out on healthy, Congestive Heart Failure (CHF) and Atrial Fibrillations (AF) subjects using their ECG signals. The entropy methods used in the work are Approximate entropy (ApE), Symbolic entropy (SyE) and Spectral entropy (SpE). ECG signals of 20 healthy subjects in the age group of 21 – 30 years were acquired using dry electrode at a sampling rate of 500 Hz for 10 minutes. Signal processing algorithms for removal of baseline wandering, power line interference and motion artefacts were applied for the raw ECG signal. The ECG signals for CHF and AF subjects in the age group of 30 – 75 years were obtained from the Physionet database. From the analysis it was found that values of ApE and SyE were highest for AF subjects and for SpE, the value was highest for healthy subjects. Further, values of all the three entropies were lowest for CHF subjects. In conclusion, it indicates that the entropy techniques are useful tools in diagnosing patients having heart disorders

Modified Pipelining Hybridization of Job Shop Scheduling

Hybridization involves generally genetic algorithm in a stage .Here instead of genetic algorithm,metaheuristics method Local search method, is applied as primary search routine, for tacklingcombinatorial search and optimization problems.The dispatching rule LPT is applied first, servingas a preprocessor. The local search methods are works on the iterative exploration of a solutionspace: at each iteration a local search algorithm start search from one solution to one of itsneighbor. The method is analysis the job shop bench mark problems. The comparison of theperformance measure is evaluated

Stacking of Hyperparameter Tuned Models for Tagging Coding Problems

Coding problems are problems that require a solution in the form of a computer program. Coding problems are popular among students and professionals as it enhances their skills and career opportunities. An AI system that would help those who practice coding problems would be highly useful and there is a huge potential for such a system. In this work, we propose a model which uses stacking of hyperparameter tuned boosting models to achieve impressive metric scores of 77.8% accuracy and 0.815 PR-AUC on the dataset that was scraped from Codeforces and Leetcode. We open source the dataset and the models developed for this work.Comment: 8 pages, 2 figure

Assessing spatial variability of soil and drawing location-specific management zones for coastal saline soils in Ramanathapuram District, Tamil Nadu

The production of crops in saline and alkali-degraded areas is difficult due to the heterogeneous and spatial variation of soil fertility.  First, their spatial variability was analyzed and maps of the spatial distribution were created using Geostatistical techniques.  The fuzzy k-mean clustering analysis was then used to define Management zones in the coastal saline soils of Ramanathapuram district in Tamil Nadu.  One hundred and fifty geo-referenced soil samples  (30 cm depth) were taken and analyzed for pH, electrical conductivity (ECe) in the saturated paste extract (USSL method), organic carbon (OC) (Walkley-Black chromic acid wet oxidation method), calcium carbonate (CaCO3) (Rapid titration method) and available phosphorus and extractable micronutrients (Multinutrients extraction method), revealing significant variation in soil characteristics throughout the coastal saline soils of Ramanathapuram district.  The most significant factors, which together accounted for four principal components and 69% of the overall variability, were pH, electrical conductivity (ECe), calcium Carbonate and available zinc.  According to Geostatistical analysis, the Exponential (pH, OC (organic carbon), P, Fe, Mn and Zn) and Stable (ECe) was the best fit semivariogram ordinary kriging model with weak to moderate spatial dependence.  Fuzzy k-mean clustering was also used to identify zone 1, zone 2 and zone 3.  For every soil property, there was a significant difference between MZ1(zone 1), MZ2(zone 2) and MZ3(zone 3).  These results also showed that cluster analysis gave farmers a chance to use location-specific nutrient management strategies by minimizing variability within the zone. The management zones can decrease agricultural inputs and environmental pollutants while increasing crop productivity.

The Arecibo Methanol Maser Galactic Plane Survey - II: Statistical and Multi-wavelength Counterpart Analysis

We present an analysis of the properties of the 6.7 GHz methanol maser sample detected in the Arecibo Methanol Maser Galactic Plane Survey. The distribution of the masers in the Galaxy, and statistics of their multi-wavelength counterparts is consistent with the hypothesis of 6.7 GHz maser emission being associated with massive young stellar objects. Using the detection statistics of our survey, we estimate the minimum number of methanol masers in the Galaxy to be 1275. The l-v diagram of the sample shows the tangent point of the Carina-Sagittarius spiral arm to be around 49.6 degrees, and suggests occurrence of massive star formation along the extension of the Crux-Scutum arm. A Gaussian component analysis of the maser spectra shows the mean line-width to be 0.38 km/s which is more than a factor of two larger than what has been reported in the literature. We also find no evidence that faint methanol masers have different properties than those of their bright counterparts.Comment: Accepted by ApJ; Revised footnote number 3 on page 8 based on private communicatio

A Search for 6.7 GHz Methanol Masers in M33

We report the negative results from a search for 6.7 GHz methanol masers in the nearby spiral galaxy M33. We observed 14 GMCs in the central 4 kpc of the Galaxy, and found 3 sigma upper limits to the flux density of ~9 mJy in spectral channels having a velocity width of 0.069 km/s. By velocity shifting and combining the spectra from the positions observed, we obtain an effective 3sigma upper limit on the average emission of ~1mJy in a 0.25 km/s channel. These limits lie significantly below what we would expect based on our estimates of the methanol maser luminosity function in the Milky Way. The most likely explanation for the absence of detectable methanol masers appears to be the metallicity of M33, which is modestly less than that of the Milky Way

Single-Echelon Supply Chain Two Stage Distribution Inventory Optimization Model for the Confectionery Industry

Abstract In this paper, a supply chain two stage distribution inventory optimization model with interactive-lateral transshipment among retailers in a particular period is considered. Interactive-lateral transshipment among retailers means that once the stocks are allocated to retailers from ware houses, we allow lateral stocks transfer among retailers if the further optimization is possible which will enable us to further minimize overall cost in the supply chain. The proposed model is formulated as a linear programming model which is validated with help of a confectionary industry data. This model is to provide an optimal inventory level for the warehouses and retailers and also, minimizing the total cost of the entire supply chain for a finite planning horizon. Mathematics Subject Classification: 90B05, 90B06, 90B50, 90C05, 62P3

Agricultural bio-waste recycling through efficient microbial consortia

In India and other countries, rice straw, a byproduct of rice production, is burned in enormous amounts, which contributes to environmental pollution and climate change by releasing greenhouse gases viz., CO2, N2O, CH4, into the atmosphere. This study aimed to accelerate the degradation of this enormous amount of agricultural biomass via microbial inoculants. Four treatments—rice straw (RS), rice straw plus water (RSW), rice straw plus water plus Pusa decomposer (RSWF), and rice straw plus water plus Tamil Nadu Agricultural University (TNAU) biomineralizer (RSWB) were used in the current investigation. The study's findings demonstrated that rice straw treated with microorganisms decomposed more quickly than RS and RSW treatments. According to EDAX spectra of elemental composition, the carbon content of rice straw in the RS, RSW, RSWF, and RSWB treatments was 33.66%, 29.75%, 13.33%, and 20.65% w/w, respectively. The RSWF treatment of rice straw was found to have the highest nitrogen concentration (0.64% w/w), followed by RSWB (0.61% w/w), RSW (0.45%) w/w, and RS (0.43% w/w). Treatments RSWF and RSWB had lower C/N ratios 20.83, and 33.85, respectively, than that RSW (66.11) and RS (78.28). The RSWF and RSWB treatments' porous, distorted, and rough surface structures provided further evidence that both microbial consortia could decompose rice straw more quickly than the RSW and RS treatments. Therefore, the results of this study imply that rice straw could be added to the soil to improve soil fertility for sustainable crop production rather than being burned