K. Sujatha ¹, P. Senthilkumaar ¹, S. Sangeetha ¹, M. D. Gopalakrishnan ¹

Affiliations
1 School of Enzymology and Environmental Toxicology, Sir Theagaraya College, Chennai-600 021, IN

Abstract

Two edible fishes, Bulls eye, Priacanthus hamrur (Percidae) and Hard tail scad, Megalaspis cordyla (Carangidae) from the waters of Royapuram coast, Chennai, Tamil Nadu were chosen for isolation of bacterial human pathogens in their gills, intestine, muscle and skin. Based on their growth characteristics on specific culture media, the following human bacterial pathogens, Escherichia coli, Salmonella typhi, Pseudomonas aeruginosa, Vibrio cholerae and Shigella dysenteriae were isolated in both the fishes. The medium of the fishes and the sediments of their habitat were furthermore collected and examined for pathogens. Different bacterial species were found in the medium that was analyzed, including the human pathogens isolated from the fishes. Surprisingly the five human bacterial pathogens harbored in the fishes were found in the medium but not in the sediment. This research is primarily to highlight the quality of these two edible fishes in the coastal waters of Royapuram, Chennai and to create awareness amid fish eating population.

Keywords

Fish, Water Pollution, E. coli, Salmonella typhi, Pseudomonas aeruginosa, Vibrio cholerae, Shigella dysenteriae, Priacanthus hamrur, Megalaspis cordyla

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S. Sangeetha ¹, K. Sujatha ¹, P. Senthilkumaar ¹, V. Kalyanaraman ¹, S. Eswari ¹

Affiliations
1 School of Enzymology and Environmental Toxicology, Sir Theagaraya College, Chennai-600 021, IN

Abstract

Nitrogen fertilizers tend to increase ammonium concentration especially in the aquatic medium. To evaluate its impact, the acute toxicity of ammonium sulphate, urea and a composite fertilizer (15:15:15) (NPK-1) was assessed in fingerlings of fresh water fish Catla catla using a static test system. The toxicity of ammonium sulphate, urea and NPK1 to C. catla increased with increasing fertilizer concentration and duration of exposure. The concentration that killed 10% (LC₁₀) and 90% (LC₉₀) of fish varied with the fertilizers. The concentrations of ammonium sulphate, urea and NPK- 1 that killed 50% of fingerlings of C. catla within 96-h (96-h LC₅₀) were 0.12, 0.19 and 0.18 g/L, respectively. Ammonium sulphate concentrations killing 50% (LC₅₀) of the fingerlings of fresh water fish Catla catlawere 0.23, 0.17, and 0.14, 0.12 g/L during 24hr, 48hr, 72hr and 96hr correspondingly. Ammonium sulphate was found to be more toxic to the juvenile fresh water fish C. catla compared to urea and NPK-1.

Keywords

Acute Toxicity, Nitrogen Fertilizers, Catla catla, Fish, Pollution

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K. Sujatha ¹, P. Muralikrishna ², M. Chandramouleeswaran ¹

Affiliations
1 Department of Mathematics, SBK College, Aruppukottai-626 101, Tamilnadu, IN
2 School of Advanced Sciences, VIT University, Vellore-632 014, Tamilnadu, IN

Abstract

In this paper, we introduce the notion of the product on Intuitionistic Fuzzy β- sub algebras in β- algebra and investigate some of their results.

Keywords

β- algebra, Cartesian Product on Intuitionistic Fuzzy β- sub Algebra

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K. Sujatha ¹, D. Shalini Punithavathani ¹, Lallawmzuala Khawlhring ¹

Affiliations
1 Government College of Engineering, Tirunelveli - 627007, Tamil Nadu, IN

Abstract

Background: In Recent years Display of HDR images on yardstick LDR Displays with Tone mapping Operators (TMO) has many issues like halo artefacts, edge preservations and visual appearance. Always there exists a issue about usage of operator with regard to the input sequence without all these factors. Objectives: In this paper a thorough analysis is carried out with 31 TMO operators. Existing study papers are up to maximum of 8 TMOs, but this paper evaluates all the 31 operators and the objective quality measure is calculated. Researchers are carried out to identify a better operator for its own applications, which motivated to do this paper, the resultant analysis provokes to the development of a new method with lesser computational time. This work can be further extended to optimization of the algorithm used in fusion of base and detail layers of sequence of input. From the analysis the naturalness, structural fidelity and Quality of the image can be improved.

Keywords

Enhancement of LDR Image, High Dynamic Range Images, Local and Global Operator, Tone Mapping Operators.

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V. Srividhya ¹, K. Sujatha ¹, R. S. Ponmagal ²

Affiliations
1 EEE/CSE Department, Center for Electronics, Automation and Industrial Research (CEAIR), Dr. M.G.R. Educational & Research Institute, Maduravoyal, Chennai, Tamil Nadu, IN
2 EEE Department, Meenakshi College of Engineering, Maduravoyal, Chennai – 560064, Tamil Nadu, IN

Abstract

Objective of the Work: The highlight of this research work is to discover the ethylene gas level used for ripening of fruits by detecting ethylene gas (C2H4 in ppm) level employing soft sensor built using image processing and Artificial Neural Networks (ANN) algorithms. Methods/Statistical Analysis: The proposed method relies on the color which denotes the various stages in ripening and in turn indicates the amount of ethylene gas required. The changes in color, texture, intensity variation, mean, variance and standard deviation extracted from the images are the features which enable the personnel to determine the amount of ethylene gas. The Feed Forward Neural Network (FFNN) is used for ethylene gas estimation. This is made possible using Back Propagation Algorithm (BPA) for training the FFNN. As a part of image processing the intensity values in color images and its variation are tracked by dithering which is used as a unique feature input to train the FFNN. Major Findings: The novelty of the proposed method depends on the FFNN estimating the ethylene gas needed for ripening process in a feed forward fashion thereby providing the precision and recall values spontaneously for every instance. Application/Improvements: Earlier a circuit with capacitance model is used to generate ethylene gas for this purpose. Nearly 51 images are considered for training and testing respectively. Testing and confirmation result shows the required precision and recall level are in range of 80 to 89% and 100% respectively.

Keywords

Back Propagation Algorithm, Ethylene Gas, Feed Forward Neural Network Feature Extraction, Image Processing.

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K. Sujatha ¹, S. Bala Krishnan ², S. Sheeba Rani ³, M. K. Bhuvana ⁴

Affiliations
1 Department of Computer Science and Engineering, Sri Krishna College of Engineering and Technology, Coimbatore – 641008, Tamil Nadu,, IN
2 Department of Information Technology, Sri Krishna College of Engineering and Technology, Coimbatore – 641008, Tamil Nadu, IN
3 Department of Electrical and Electronics Engineering, Sri Krishna College of Engineering and Technology,Coimbatore – 641008, Tamil Nadu, IN
4 Sri Krishna College of Engineering and Technology, Coimbatore – 641008, Tamil Nadu, IN

Abstract

Objective: In order to prevent the theft of authentication of the keywords and to preserve the biometric authentication a method is derived to secure the pattern. Methods/Statistical analysis: An efficient identification and authentication methods are implemented by using the dorsal vein recognition system which is very popular among the researchers of the world. By identifying the unique pattern of the hand vein, the features are extracted from the images and pattern is framed and dimension reduction is based on the system application. Application: This simple model can be used in reduction of dimensionality and the noise can be removed from the biometric pattern which helps to have high security. Findings: This paper contributes on image acquisition, preprocessing techniques, feature extraction in hand vein authentication system.

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S. Balakrishnan ¹, J. Janet ¹, K. Sujatha ², S. Sheeba Rani ³

Affiliations
1 Department of Information Technology, Sri Krishna College of Engineering and Technology, Coimbatore – 641008, Tamil Nadu, IN
2 Department of Computer Science and Engineering, Sri Krishna College of Engineering and Technology, Coimbatore – 641008, Tamil Nadu, IN
3 Department of Electrical and Electronics Engineering, Sri Krishna College of Engineering and Technology, Coimbatore – 641008, Tamil Nadu, IN

Abstract

Objectives: To make a fully automated algorithm that is based on simple and quick steps, which produces consistent output for the same inputs. Methods/Statistical Analysis: For thorax and lung segmentation, region growing based method is used to segment the region of interest. The missing parts of the lungs are reconstructed using morphological operations. After that, nodules are detected based on the features of the reconstructed image. Artificial Neural Network has been used for classifying the images. Findings: An aggregate of 100 pictures with determination of 512 × 512 pixels with eight bits for every shading channel are caught. 90% affectability was obtained with 0.05 false positives for each picture. Application/Improvements: This framework distinguishes the phase of lung malignancy. The outcomes demonstrate that the tumors are of various measurements. By estimating the measurements of the tumor the lung disease stage can be recognized precisely utilizing the proposed technique. The outcomes indicate great potential for lung growth identification at beginning time.

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S. Sheeba Rani ¹, J. Janet ², S. Balakrishnan ², K. Sujatha ³

Affiliations
1 Department of Electrical and Electronics Engineering, Sri Krishna College of Engineering and Technology, Coimbatore – 641008, Tamil Nadu, IN
2 Department of Information Technology, Sri Krishna College of Engineering and Technology, Coimbatore – 641008, Tamil Nadu, IN
3 Department of Computer Science and Engineering, Sri Krishna College of Engineering and Technology, Coimbatore – 641008, Tamil Nadu, IN

Abstract

Objectives: To model a novel ceaseless client validation method to authorize the client regardless of their body position before the capturing system. The system ceaselessly validates the client with their various soft anthropometric parameters such as (e.g. wearables and skin) in addition to hard biometrics. Methods/Statistical Analysis: The proposed system mechanically stores in the soft anthropometric parameters each time the client logs in and integrate the anthropometric parametric features along with the conventional face traits for verification thus fusing the combination of hard and soft biometric attributes to attest a client ceaselessly. The methodology comprises of various modes such as initialization, validation and regeneration. Findings: Various samples of facial colour features and user’s cloth colour features are used as soft biometrics in this system for authorization. The experimental results of AR show the extensive improvement over the existing methods. Application/Improvements: This methodology eliminates the challenges faced in face recognition due to different expressions and postures, lighting effects. Thus the key discriminating features are authenticated using hard and soft biometrics thus making it a high secure technology.

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