Informatics Publishing Limited

K. Shanthi ¹, A .P. Subapriya ², R. Kalaivani ³

Affiliations
1 NIIT, IN
2 SCAD College of Engineering and Technology(Affiliated to Anna University, Thirunelveli) in Thirunelveli, Tamilnadu, IN
3 Computer and Communication Engineering, IN

Abstract

This paper provides the sender of email the power to undo his sent mail. I provide my own idea in implementing this undo function in sending mails with my own protocol called the USEUndo Sent E-mail. This is achieved by adding an extra functionality to the domain's SMTP server and the message can be pulled by both the sender and receiver from the POP3/IMAP server. IMAP (Internet Message Access Protocol) -is a standard protocol for accessing email from your local server. The POP (Post Office Protocol 3) protocol provides a simple, standardized way for users to access mailboxes and download messages to their computers. The HTTP protocol is not a protocol dedicated for email communications, but it can be used for accessing your mailbox. If the sender pulls the mail first, then it means he has successfully retrieved the mail and if the receiver pulls the mail first, then it means the receiver has read the mail and the mail cannot be retrieved. We achieve this by implementing the USE protocol.

Keywords

HTTP, IMAP, POP, SMTP, USE.

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P. S. Meenakshi ¹, R. Kalaivani ¹

Affiliations
1 Sankara College, Coimbatore, IN

Abstract

One of the fundamental difficulties that arise in several fields, comprising pattern recognition, machine learning and statistics, is clustering. The concept of green computing has attracted much attention recently in cluster computing. However, previous local approaches focused on saving the energy cost of the components in a single workstation without a global vision on the whole cluster, so it achieved undesirable power reduction effect. Other cluster-wide energy saving techniques could only be applied to homogeneous workstations and specific applications. The concept of green computing is a novel approach that uses live migration of virtual machines to transfer load among the nodes on a multilayer ring-based overlay. This scheme can reduce the power consumption greatly by regarding all the cluster nodes as a whole. Also that it can be applied to both the homogeneous and heterogeneous servers. Experimental measurements show that the new method can reduce the power consumption by 74.8% over base at most with certain adjustably acceptable overhead. The basic data clustering problem might be defined as finding out groups in data or grouping related objects together. A cluster is a group of objects which are similar to each other within a cluster and are dissimilar to the objects of other clusters. The similarity is typically calculated on the basis of distance between two objects or clusters. Two or more objects present inside a cluster and only if those objects are close to each other based on the distance between them. The major objective of clustering is to discover collection of comparable objects based on similarity metric. On the other hand, a similarity metric is generally specified by the user according to his requirements for obtaining better results. So far, there is no such technique available which absolutely fits for all applications. Some of the major difficulties concerning the existing available clustering approaches are that they do not concentrate on the entire needs effectively and require huge time complexity in case of clustering a great number of dimensions and bulky data sets. Efficiency of a particular clustering approach chiefly based on the definition of the distance, means that the measure of distance between the two objects in a particular cluster should be well defined using effective distance measures. Also it is necessary to know about the effect of constraints in clustering the objects. The use of constraints in clustering along with the effective distance measures will definitely provide better clustering results. So in order to provide better clustering approaches that fits for all applications and to improve the efficiency of data clustering, this paper proposes a comparative analysis of various algorithms to show the efficient data clustering algorithm.

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M. Lydia Packiam Mettilda ¹, R. Lawrance ², R. Kalaivani ³

Affiliations
1 Department of Computer Application, Ayya Nadar Janaki Ammal College, Sivakasi, IN
2 Computer Application Department, Ayya Nadar Janaki Ammal College, Sivakasi, IN
3 Department of Computer Science and Information Technology, Ayya Nadar Janaki Ammal College, Sivakasi, IN

Abstract

With the advancement in technology, one thing that concerns the world and especially in the developing countries is the tremendous increase in population. With such a rapid rate of increase, it is becoming difficult to recognize each and every person because we have to keep up photos either in digital or hard copy format of every person at different time periods of his/her life. Sometimes database has the required information of that particular person, but it’s of no use as it is now obsolete. Deciding age of a person from digital photography is an intriguing problem. Age changes cause many variations in visible of human faces. Many aspects affect the appearance of a person’s face during the process of growing older. The aging process will explain with many factors such as health, living style, living place and weather condition etc. Face is a non-intrusive recognition, without user co-ordination able to recognize the person. Age classification system is generally composed of feature extraction and classification. It is used to estimate the age of a person from his/her face features. For the aging feature extraction, face images interpreted as decomposition of optimized wavelet transform with 49 feature vectors using Daubechies wavelet and the classifier of supervised neural network to discriminate the ranges of ages. The work is to classify the age range into child (1-10), teenage (11-20) young (21-30), middle aged (31-50) and old (51 and above).

Keywords

ASM, Wavelet, Age Classification, Neural Network.

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R. Kalaivani ¹, C. Devi Arockia Vanitha ², R. Lawrance ³, M. Lydia Packiam Mettilda ⁴

Affiliations
1 Department of Computer Science & Information Technology, Ayya Nadar Janaki Ammal College, Sivakasi 626 124, Tamilnadu, IN
2 Computer Science Department, The S.F.R. College for Women, Sivakasi 626123, Tamilnadu, IN
3 MCA Department, Ayya Nadar Janaki Ammal College, Sivakasi 626 124, Tamilnadu, IN
4 Department of Computer Application, ANJA College, Sivakasi 626 124, Tamilnadu, IN

Abstract

Most of the real world problems in engineering, medicine, industry, science and business also involve data classification. Classification is a supervised machine learning technique used to predict group membership for data instances. Pattern classification problems belong to the category of supervised learning. Pattern Classification involves assigning a label to a given input data. Neural Networks are an effective tool in the field of pattern classification, using training and testing data to build a model. Training neural networks in classification problems, especially when biological data are is a very challenging task. The protein superfamily classification problem, which consists of determining the superfamily membership of a given unknown protein sequence, is very important for a biologist for many practical reasons, such as drug discovery, prediction of molecular function and medical diagnosis. The objective of this work is creating a classification model for classifying data using Multilayer feed forward network. It contain two phases. First, classifier model was build for iris plant classification. Second, classifier model was build for protein sequence classification to know the organism of protein and family of the given protein sequence.

Keywords

Data Mining, Pattern Classification, Neural Network, Back Propagation, Iris Plant, Bioinformatics, Protein Sequence.

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R. Kalaivani ¹, P. Thangaraj ²

Affiliations
1 Institute of Road and Transport Technology, Erode, Tamilnadu, IN
2 Department of CSE, Bannari Amman Institute of Technology, Sathyamangalam, Tamilnadu, IN

Abstract

Nowadays, satellite image processing plays a crucial role for the research developments in many fields of study including Astronomy, Remote Sensing, GIS, Agriculture Monitoring and Disaster Management. The remotely sensed images are utilized in many of the researches with the aim of predicting natural disasters so that essential precautions can be taken to protect the environment. Besides the other, the water resource analysis plays a vital role in these researches. Traditionally, lots of methods are utilized for the analysis and determination of the level of water in water resources. In this work, the river water resource is analyzed to determine the stage of the water level using multilayer feed forward and radial basis feed forward networks and their performance is measured. The existing works are not effective because they determine only the changes that occur in the water level and does not translate them into meaningful results that indicates its status i.e., whether it is in the danger zone or not.

Keywords

Satellite Image Processing, River Stage, Back Propagation, Radial Basis Feed Forward Network, Sensitivity, Specificity, Accuracy.

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A. Vinoth ¹, V. Balakrishnan ¹, R. Kalaivani ¹, P. Madhanraj ², N. Nadimuthu ³

Affiliations
1 Department of Biotechnology, Thanthai Hans Roever College of Arts and Science, Perambalur - 621 212, Tamil Nadu, IN
2 Indian Biotrack Research Institute, Thanjavur, Tamil Nadu, IN
3 P.G. Department of Plant Science, Avvaiyar Government College for Women, Karaikal 609 602, Puducherry U.T., IN

Abstract

Oil pollution is worldwide major problem in every environment and hence the world is need of a perfect solution for prevention or recovery so, the present investigation was carried out to detect the spent lubricant oil degradation potentional of indigenous fungi in lab level by measuring the growth and analysis the treated sample using FTIR. Soil sample was randomly collected in the different location at railway tracks in Thanjavur junction soil sample are serially and 10^-2 is used for plating technique in PDA medium. After incubation the isolates were obtained and they are Aspergillus terreus, Aspergillus flavus and Aspergillus niger. Oil degrading ability was detected supplying raw spent oil in PDA medium and incoprporated in PD broth at the concentration of (5%.10%, 15% and 20%), detection shows that no fungal cored use raw oil as source of nutrient. In PDA plate's visual detection of zone due to the degradation was noticed. It was maximum by Aspergillus flavus follwed by Aspergillus terreus and Aspergillus niger. In PD broth supplemented with different spent oil concentration (5%,10%,15% and 20%), after 14 days of incubation (30°C), as a visual the biomass of each fungal culture was determined the biomass of different species of fungi in different concentration oil showed growth but with variation the higher mycelial biomass was recorded by Aspergillus flavus. The FT-IR analysis results shows that is major difference in the peak formation between the tested samples which shows that fungal species has utilized or degraded the oil hydrocarbon. Differently as per their metabolize activity.

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R. Kalaivani ¹, K. Sudhagar ², P. Lakshmi ³

Affiliations
1 DEEE, Vel Tech Multi Tech Dr. Rangarajan Dr. Sakunthala Engineering College, Avadi, Chennai - 600062, Tamil Nadu, IN
2 Murugappa Polytecnic College, Avadi, Chennai - 600062, Tamil Nadu, IN
3 DEEE, CEG, Anna University, Chennai - 600025, Tamil Nadu, IN

Abstract

This paper presents a novel Neural Network (NN) based vibration control of a Vehicle Active Suspension System (VASS) when subjected to road disturbance for enhancing the travelling comfort to the passengers. The simulation for the vibration control of VASS with Proportional Integral and Derivative (PID) controller is used for training the NN. The nonlinearities of the system parameters can be effectively handled by the NN and also it can deal with unfocused data by considering the prejudiced phenomena such as logical reasoning and perception beyond its domain. The idea of this work is to design, simulate and compare the performance of NN based VASS with that of the uncontrolled suspension system (passive) and the VASS controlled with PID controller. The Root Mean Square (RMS) value of body acceleration as the performance index for genetic optimization, the simulation is carried out using MATLAB/SIMULINK software. Simulation results such as sprung mass displacement, body acceleration, suspension deflection, tyre deflection and Power Spectral Density (PSD) of body acceleration shows the effectiveness of NN in suppression of the vibration of vehicle body compared to passive system, PID based VASS and optimized PID controller.

Keywords

Genetic Algorithms, Neural Networks, Simulation, Suspensions, Vibration Control

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R. Kalaivani ¹, R. Krishnapriya ²

Affiliations
1 Department of Biotechnology & Bioinformatics, Dhanalakshmi Srinivasan College of Arts & Science for Women, Perambalur-621212. Tamil Nadu, IN
2 Department of Biotechnology, Meenakshi Ramasamy Arts & Science College, Thathanur-621804, Ariyalur, Tamil Nadu, IN

Abstract

Sponges are the commonest photosynthesizing host organisms in waters with relatively poor supplies of food particle. The sponges contain the bioactive compounds that have potential medical importance. In the present study, the potent antibacterial extra cellular products were isolated from endosymbionts. The isolates showed inhibitory interactions with various gram positive and negative bacteria. The antibacterial activity of the sponge extract was determined for 5 species of gram positive bacteria Acetobacter pasteuriances, Bacillus subtilis, Lactobacillus acidophilus, Klebsiella species, Lactococcus lactis and 2 species of gram negative bacteria Proteus vulgaris, Pseudomonas fluorescence. The extract of Sigmadocia medussa contained potential antibacterial agents. The maximum inhibition zone was produced by the extract against gram positive bacteria, Lactobacillus acidophilus was found to be 1.10cm and gram negative bacteria, and Pseudomonas fluorescence was found to be 2.30cm. The true bacterial endo-symbionts may SES1- SES10 influence the synthesis of secondary metabolites of the host Sigmadocia medussa.

Keywords

Sponges, Endosymbionts, Sigmadocia Medussa, Secondary Metabolites. Inhibition Zone.

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R. Kalaivani ¹, P. Saranya ²

Affiliations
1 School of Pharmaceutical Sciences, Vels University, Chennai, Tamilnadu, IN
2 Department of Pharmacy Practice, School of Pharmaceutical Sciences,Vels University, Chennai, Tamilnadu, IN

Abstract

Off-label is defined as any drug use outside the terms of product license; while the unlicensed use refers to using a drug in children when it has not received marketing authorization for use in them. The objective of the study was to determine the attitude and experience of community pharmacists towards off-label and unlicensed prescriptions for the pediatric population. This study was carried out as a prospective observational study for a period of six months at the community pharmacies in and around Chennai. Validated questionnaire to assess the attitude and experience of community pharmacists towards unlicensed and off-label prescriptions for the paediatric population was given to those community Pharmacists who have registered in the State Pharmacy Council as Pharmacist. Questionnaires issued were self administered by the community pharmacists and the answers recorded by them were collected and then assessed. Over 70% of respondents were familiar with the concept of off-label prescribing, primarily through dispensing experience rather than education. Over 60% of respondents had been asked by the public to sell paediatric over-the-counter medicines, such as antihistamines, analgesics and steroid preparations for off-label use. Most common off-label drug was paracetamol being 32% (BNFC) of all prescribed in this manner. Most common information sources was British national formulary for children (BNFC), Current index medical specialities(CIMS) and local formularies. The majority of respondents (74%) admitted to being familiar with the concept of off-label prescribing .The majority of respondents, 88% agreed or strongly agreed that the pharmacist has a responsibility to inform the prescriber that they are prescribing off-label medicines for children, and 32% unsure that pharmacist also has a responsibility to inform the parents that the medicines prescribed for their children are off-label. Dispensing labeled and licensed drugs in pediatric patients should be promoted among the community pharmacist as well as pediatricians in order to avoid exposing children to unnecessary risk. Participation in Continuing Medical Education should be encouraged among community pharmacist to keep their knowledge updated.

Keywords

Off-Label, Unlicensed, Community Pharmacy, Pediatrics, Questionnaire, Attitude

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Dileep Pulugu ¹, P. Anusha ², Ratan Rajan Srivastava ³, R. Kalaivani ⁴, Subharun Pal ⁵

Affiliations
1 Department of Computer Science and Engineering, Malla Reddy College of Engineering and Technology, IN
2 Department of Electronics and Communication Engineering, R.M.K. Engineering College, IN
3 Department of Computer Science and Engineering, B.N. College of Engineering and Technology, IN
4 Department of Computer Science, National College, IN
5 SSM Research Center, Swiss School of Management, CH

Abstract

Video surveillance systems play a crucial role in ensuring public safety and security. However, the traditional methods of surveillance often fall short in effectively identifying individuals, particularly in crowded or dynamic environments. This research addresses the limitations of conventional video surveillance by proposing a machine learning-based facial recognition system. The increasing demand for robust security measures necessitates the development of advanced technologies in video surveillance. Facial recognition has emerged as a promising solution, but existing systems struggle with accuracy and efficiency. This research aims to bridge these gaps by leveraging machine learning techniques for facial recognition in video surveillance. Conventional video surveillance struggles with accurate and rapid identification of individuals, leading to potential security lapses. This research addresses the challenge of enhancing facial recognition accuracy in real-time video feeds, especially in scenarios with varying lighting conditions and occlusions. While facial recognition has gained traction, there is a significant research gap in the implementation of machine learning algorithms tailored for video surveillance. This study aims to fill this void by proposing a novel methodology that combines deep learning and computer vision techniques for robust facial recognition in dynamic environments. The proposed methodology involves training a deep neural network on a diverse dataset of facial images to enable the model to learn intricate facial features. Additionally, computer vision algorithms will be employed to handle challenges such as occlusions and varying lighting conditions. The model's performance will be evaluated using real-world video surveillance data. Preliminary results demonstrate a significant improvement in facial recognition accuracy compared to traditional methods. The machine learning-based system exhibits enhanced performance in challenging scenarios, showcasing its potential for practical implementation in video surveillance systems.

Keywords

Facial Recognition, Machine Learning, Video Surveillance, Deep Learning, Computer Vision

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