S. Lakshmi ¹, R. Siva Kumar ², S. Rajendran ³

Affiliations
1 Jeppiaar Engineering College, Chennai, IN
2 Barathiar University, IN
3 Department of Chemistry, R. V. S. School of Engineering and Technology, Dindigul-5, IN

Abstract

The blue green microalgae Spirulina platensis is an important source of nutrients. An important obstacle for the production of Spirulina is Rotifer. In this paper we present a method for automated identification and recognition of rotifer contamination in Spirulina using image processing techniques. Getting the expert's advice is an essential one to improve the production. Our primary objective is to provide high nutrients Spirulina free from contaminations and secondary objective is to solve the quality issue by identifying rotifer contaminations at the earliest and giving suggestions through the mobile phones. Using microscopic examination for identifying rotifier in live culture is time consuming and manmade process. There is a chance for man made error and our new technique is machine made and the errors to be minimized. Existing system need qualified persons for operation and our proposed system can be operated by anyone. We examine lab scale Spirulina culture through both existing and new techniques for recognizing the rotifer. Our proposed tool for identifying contaminations at beginning stage is easy to eradicate the contaminations from live culture. It will be helpful to biologist to take necessary actions against contaminations of the same before further multiplications of contaminations. According to the Survey of Sun food Super Food, in 2020 the expected world wide Spirulina production is about 220 thousand tons. Hence Spirulina can be a solution for solving the world nutrition problems due to its very high growth rate and high nutritional value. Our research-automatic identification of contamination in algae through the processing of mobile phone images is an easiest way for improving and evaluating the growth of Spirulina for effective cultivation of algae.

Keywords

Automatic Detection and Contamination, Image Processing, Recognition, Rotifer, Spirulina.

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S. Lakshmi ¹, R. S. D. Wahida Banu ¹

Affiliations
1 Anna University, Chennai - 600025, Tamil Nadu, IN

Abstract

Background: Vanet the recent emerging technology in the recent industry has grabbed the attention with advanced techniques and extricate framework of sophisticated equipments. Initially absence of an infrastructure in this network has communication constraints for the nodes involved therein. Adding to this the dynamic topology makes the network more vulnerable for potential targets of security and reliability of data diffusion within these nodes. The communication standard i.e. 802.11p have some optional channel rejection in the Orthogonal Frequency Division Multiplexing in the Physical layer which motivated to work on the reliability methods of data dissemination. Methods: To start with the hidden terminal issues of these networks have to be addressed which can be resolved by frame capture. This frame capture quality in turn is determined by the Contention window of the Physical layer. Hence an adaptive mechanism that involves forward Error correction (AFEC) which helps to overcome packet losses in an efficient way in midst of channel fluctuation, burst packet loss. The results are simulated in NS2 (2.34) with static packet size of 512 bytes. Findings: The experimental results demonstrated that the FEC mechanism is more adaptive in adjusting and controlling the data redundancy across the network for static and dynamic channel fluctuations. The redundancy rate was further reduced with an adaptive technique on the Contention Window size, which had considerable effects of every transmission on the delay, through put and jitter. The centralized FEC algorithm is set on an adaptive platform where each vehicle updates its back off window size at the end of each Observation Time depending on the priority of the message received. The feasible part of this algorithm is that it can be implemented on the MAC layer, which has a Reception Module. Consequently, the proposed mechanism under various network conditions performs well in terms of QoS for emergency messages than the conventional methods for a less volume of data. Application/Improvements: The algorithm can be analyzed from a traffic scenario of two-way highway and rural areas. The progress of the work can also be carried out for multimedia messages.

Keywords

Contention Window, Data dissemination, Forward Error Correction Mechanism, QoS of message, Vanets

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