Informatics Publishing Limited

S. V. Sree Charulatha ¹, R. Gowtham ²

Affiliations
1 MNM Jain Engineering College, IN
2 IEEE, IN

Abstract

Sentiment analysis aims to detect attitude and feelings of the opinion holder for the given reviews. Reviews are user generated content about wide variety of commodities available on the social media. It is useful for both the consumer and business people. Sentiment Classifier (SC) might classify reviews as Positive or Negative based on the sentiment expressed in review. SC are domain dependent (same opinion word gives different meaning or contrast polarity in different domain). Cross domain sentiment classification problem were challenges of training a classifier from one or more domain and applying the trained classifier on different domain. The classifier which automatically classifies the reviews as positive sentiments and negative sentiments in different domain is handled. The user reviews from social media is preprocessed for extracting the opinion word from reviews and we classify the word as dependent and independent word using spectral feature alignment by constructing a bipartite graph. After the classified word is check for its polarity and feature based summary.

Keywords

Cross Domain Sentiment Classification, Domain Adaptation, Bipartite Graph, K-Means Clustering, Ensemble Classifier, Hierarchical Clustering.

Full Text

     

Sonali McDermid ¹, R. Gowtham ², K. Bhuvaneswari ², Geethalakshmi Vellingiri ², Lakshmanan Arunachalam ²

Affiliations
1 Department of Environmental Studies, New York University, New York, US
2 Agro Climate Research Centre, Tamil Nadu Agricultural University, Coimbatore 641 003, IN

Abstract

This study evaluates the impacts of climate change on maize yields in Tamil Nadu, and assesses the efficacy of adaptation strategies, using a novel multi-climate, multi-crop model approach based on AgMIP Protocols (www.agmip.org). While the climate models displayed consistent changes to rainfall and temperature, substantial uncertainty exists between the different climate-crop model responses that warrant further study. Adaptation strategies proved beneficial under a current climate context, but showed diminished efficacy under future climate conditions. We recommend that future work focus on identifying the main sources of climate-crop model uncertainty, and that additional work may focus on more transformative adaptation measures.

Keywords

Adaptation, Climate Change, Crop Model, Climate Model, Maize.

Full Text

   

S. V. Ranganayakulu ¹, A. Kucheludu ¹, R. Gowtham ¹, B. Ramesh Kumar ²

Affiliations
1 Center for Non Destructive Evaluation, Gurunanak Institutions Technical Campus, Hyderabad-501506, Andhra Pradesh, IN
2 Institute for Plasma Research, Bhat, Gandhinagar-382428 Gujarat, IN

Abstract

Aluminum alloys consist of different grade namely HE-15, 30, and 20 respectively. These alloys are selected from 6XXX series of aluminum group. All the alloys are fabricated from machining into rectangle shape in the form of 150mm in length, 120mm in width and 12mm in thickness. The main concept arises during the interpretation of alloys is defects are notified. The defects are traced out from the aluminum alloys by NDT methods, ultrasonic method and liquid penetrant method. These NDT techniques are conducted on the all aluminum alloys according to ASNT procedure to trace out defects in the materials. After, pulse-echo method of A-scans and experimented on the aluminum alloys, On the other hand water soluble dye penetrant test also performed to trace out the surface defects. Lastly, various orientations of defects are mapped out through the implementation of NDT methods and remedy behind the defects are traced out due to improper handling of welding process.

Keywords

Aluminum Alloys, NDT Methods, Pulse-Echo Technique, Liquid penetrant Method, A-Scan.

Full Text

   

R. Gowtham ¹, P. Gopinath ²

Affiliations
1 BDS, Saveetha Dental College, Chennai, IN
2 Department of Microbiology, Saveetha Dental College, Chennai, Tamil Nadu, IN

Abstract

PVL and γ -haemolysin are considered to be members of a toxin family known as synergohymenotropic toxins, as they act on cell membranes by the synergy of two proteins that form a pore. Only 2% of S. aureus isolates produce PVL, while γ -haemolysin is produced by more than 99% of S. aureus isolates. PVL is the most leukocytolytic toxin in the family, however it does not exhibits no haemolytic activity on human erythrocytes. A sum of 20 clinical isolates of S. aureus were subjected to antibiotic sensitivity pattern followed by the detection of pvl gene by PCR. We have observed increased resistance to most of the routinely used antibiotics and 10% of our isolates found to have pvl gene. As this gene is directly associated with skin and soft tissue infections by S. aureus, our two isolates may even cause such infections, although none of these strains were not obtained from cutaneous lesions.

Keywords

Staphylcoccus Aures, Pvl Gene, PCR.

Full Text

     

V. S. K. Vanama ¹, Mohamed Musthafa ², Unmesh Khati ², R. Gowtham ², Gulab Singh ², Y. S. Rao ²

Affiliations
1 Centre for Urban Science and Engineering, Indian Institute of Technology Bombay, Mumbai 400 076, IN
2 Centre of Studies in Resources Engineering, Indian Institute of Technology Bombay, Mumbai 400 076, IN

Abstract

In August 2018, the southern Indian state of Kerala received unusually heavy rainfall leading to largescale flooding and destruction. Reliable flood inundation maps derived from remote sensing techniques help in flood disaster management activities. The freely available Sentinel-1A/B SAR data have the potential for flood inundation mapping due to its all-weather imaging capability. In this study, temporal dual-pol Sentinel-1 SAR data have been utilized. Single-date ALOS-2/PALSAR-2 commercial SAR data were also used to fill the gap between Sentinel-1 acquisitions during the peak flood-period. Two flood-mapping approaches, viz. rule-based classification in case of temporal SAR data and histogram-based thresholding approach in case of single-date imagery, were utilized in the study. Also, flood inundation mapping with different data constraints, i.e. availability of single-date and multi-date imagery has been analysed and discussed. The obtained results were validated with multiple data sources like survey data and secondary data from government agencies. An overall accuracy of 90.6% and a critical success index of 81.6% were achieved with the proposed rule-based classification approach. This study highlights the potential of the combination of Sentinel-1 and ALOS-2/PALSAR-2 data for flood inundation mapping.

Keywords

Disaster Management, Floods, Inundation Mapping, Remote Sensing, Rule-based Classification.

Full Text

   

S. Kokilavani ¹, S. P. Ramanathan ¹, Ga. Dheebakaran ¹, N. K. Sathyamoorthy ¹, N. K. Maragatham ¹, R. Gowtham ¹

Affiliations
1 Agro Climate Research Centre, Tamil Nadu Agricultural University, Coimbatore 641 003, IN

Abstract

To assess the drought hazard for different agro-climatic zones of Tamil Nadu (TN), India, the present study deals with temporal trend and spatial pattern of drought over the period 1981–2019. Standardized Pre­cipitation Index (SPI) has been used to detail the geographical variations of drought intensity, duration and frequency at multiple time steps. The spatial rainfall variability of the Southwest monsoon (SWM) ranged from 69.3 mm (Tuticorin) to 772.8 mm (the Nilgiris), and that for the Northeast monsoon (NEM) ranged from 277.8 mm (Krishnagiri) to 825.9 mm (Nagapattinam), while annual rainfall variability ranged from 558.8 mm (Tuticorin) to 1466.8 mm (the Nilgiris) for TN. Irrespective of all the regions, the frequency of moderate drought occurrence was higher compared to other drought nomenclature. The NEM season recorded on par and higher number of drought occurrences with respect to SWM season. Out of 39 years, TN experienced severely dry to extremely dry climate during 2002. The result underlines the potential of SPI in drought identification and also revealed that the rainfall is strongly linked to drought policies and measures imple­mented for the state.

Keywords

Northeast monsoon, rainfall, southwest monsoon, spatial variability, standardized precipitation index

Full Text

   

S. Sivaranjani ¹, V. Geethalakshmi ¹, S. Pazhanivelan ¹, J. S. Kennedy ¹, S. P. Ramanathan ¹, R. Gowtham ², K. Pugazenthi ¹

Affiliations
1 Tamil Nadu Agricultural University, Coimbatore 641 003, India., IN
2 Indian Farmers Fertilizers Cooperative Limited, Coimbatore 641 003, India., IN

Abstract

Hyperspectral remote sensing captures images in multiple wavelengths and is widely used to detect plant stress in agriculture. A study was conducted on brown planthopper (BPH) infestation in rice at various temperature regimes (15°C, 20°C, 25°C, 30°C and 35°C). The experimentation was done in the Environmental Control Chamber, Tamil Nadu Agricultural University, Coimbatore, India. The field spectroradiometer and vegetation indices were used to study the early and late infestations of BPH in rice. The results reveal that reflectance at certain wavelengths (550, 670 and 700 nm) indicates plant stress. Among the vegetation indices, MCARI performed better than NDVI, PRI, NDRE and SR for the detection of early and late infestation of BPH. Hence, hyperspectral reflectance from rice has been used to detect pest damage and improve management policies.

Keywords

Brown planthopper, hyperspectral sensor, Plant stress, rice, vegetation indices.

Full Text