The 11th Dimensional super power man from the short story Lion's Tail

Dr. C.S. Lakshmi uses the pen name Ambai for publishing Tamil fiction. Ambai, a Sahitya Akademi Award winner in 2021, has written works with feminist themes. A skilled short story writer. It is only possible for a few writers to mix science and novel short stories. Embedding modern scientific theories in the short story, Ambay has created a short story called "Lion's Tail" without compromising his literary taste. This short story gives an understanding of the eleventh dimension related to physics theories such as the Theory of Everything, M Theory, and String Theory. Are we still alive after the death of Mr. Haror, a Germany-based Sri Lankan writer named Rajshiva, on Facebook in 2014? Ambai's narration has helped with the article posted under the title. This article was reposted the same year by Saravana Dev in the Ekara Tamil Repository. The earth we live on has three dimensions. Scientists like Einstein confirmed the fourth dimension of spacetime. His Theory of Everything was followed by String Theory and M Theory. Physicists believe that eleven dimensions are the final result of all these theories. They suggest that life may exist in this first dimension and that they may have different energies than humans living on Earth. A cyborg is a combination of man, animal, and machine. It can also be considered a ghost. The aim of the article is to show that the story of "Lion's Tail" is written with the hypothesis that a creature in the eleventh dimension might be like a cyborg. In this short story, concepts and details about the eleventh dimension, the nature of the creatures living there, and the morphology, character, and power of the character Achyuth, who is a cyborg, are explained. M theory and string theory rank as nominal theories. In this short story, concepts and details about the eleventh dimension, the nature of the creatures living there, and the characters are explored. The power of the character Achyut, who is a cyborg, is explained. M theory and string theory rank as nominal theories. Mythical characters inherit concepts of birth and death, and concepts of female space are also seen. The short story is an analogy that takes science and combines it with traditional ideas

Error Resilient Multipath Video Delivery on Wireless Overlay Networks

Real time applications delivering multimedia data over wireless networks still pose many challenges due to high throughput and stringent delay requirements. Overlay networks with multipath transmission is the promising solution to address the above problems. But in wireless networks the maintenance of overlay networks induce additional overheads affecting the bulky and delay sensitive delivery of multimedia data. To minimize the overheads, this work introduces the Error Compensated Data Distribution Model (ECDD) that aids in reducing end to end delays and overheads arising from packet retransmissions. The ECDD adopts mTreebone algorithm to identify the unstable wireless nodes and construct overlay tree. The overlay tree is further split to support multipath transmissions. A sub packetization mechanism is adopted for multipath video data delivery in the ECDD. A forward error correction mechanism and sub-packet retransmission techniques adopted in ECDD enables to reduce the overhead and end to end delay. The simulation results presented in this paper prove that the ECDD model proposed achieves lower end to end delay and outperforms the existing models in place. Retransmission requests are minimized by about 52.27% and bit errors are reduced by about 23.93% than Sub-Packet based Multipath Load Distribution

A study on management of maternal anemia with infusion of intravenous iron sucrose and its outcome in management of anemia

Background: In India, women become pregnant with low baseline hemoglobin level resulting in high incidence of moderate to severe anemia in pregnancy where oral iron therapy cannot meet the requirement. Pregnant women with moderate anemia are to be treated with parenteral iron therapy. The aim of the study is to the infusion of intravenous iron sucrose and its outcome in the management of anemia.Methods: Totally 100 pregnant females were included in the study. The study period was from January 2018-July 2018 at vanavil medical center in Chennai. 50 Patients of Group A was given oral iron tablets containing100mg of elemental iron. 50 patients of Group B was given a total of 1000 mg of intravenous iron sucrose divided into five doses of 200 mg each at weekly intervals. Estimation of hemoglobin was started 4 weeks after commencement of iron therapy and then repeated every 4 weeks till 36 weeks of gestation, pre-delivery and postpartum.Results: Target hemoglobin levels were achieved in 4 weeks’ time in 19 (76%) patients in the iron sucrose group as compared to 08 (32%) of patients in the oral iron group. There was a significant improvement in the various hematological parameters in iv sucrose group as compared to patients in the oral iron group. There were no significant allergic reactions in iv sucrose group.Conclusions: Our results showed that intravenous iron sucrose therapy was effective to treat moderate anemia in pregnant women. Intramuscular preparations are known to be associated with local side-effects. Iron sucrose complex iv therapy was with negligible side effects. It caused a rapid rise in hemoglobin level and the replacement of stores was faster. Long term comparative studies are required to assess if they can be used at a peripheral level

A COMPARATIVE METHOD OF IOT ARCHITECTURES, CHALLENGES, PRIVACY AND SECURITY ISSUES

 It has been anticipated that all the different things of our surroundings to be under the internet. At current internet is a global network of computing or computer devices. The Idiom IoT is the scope of the internet is to be prolonged outside computer devices being interconnected to different things. Internet of Things is a categorization or classification where interconnects these non-living things like devices that can club together then try to communicate or to establish a protocol between them that they can effectively communicate among themselves and they can perform in a good manner without human intervention. As of now there is no efficient usage of IoT framework due to its now and then remodeling strategies, Due to heavy usage of IoT framework there is lot more to concern about security and privacy. This particular article deals with various IoT framework and their working and challenges of IoT framework

An Investigation of Ultra-Wideband Filters for Cognitive Radio Networks

The requirement for radio spectrum has been increasing and this has resulted in the materialization of wireless applications with enhanced features and higher data rate. The spectrum is scant, and the current radio spectrum regulation is making its use inefficient. This necessitates the development of new dynamic spectrum allocation policies to better exploit the existing spectrum. According to the present spectrum allocation regulations, specific frequency bands are allocated to particular services and only approved users are granted access to licensed bands. Cognitive radio (CR) is expected to modernize the mode spectrum is allocated. In a CR network, the intelligent radio part allows secondary users (unlicensed users) to access spectrum bands allocated to the licensed primary users with the avoidance of interference. A solution to this inefficiency has been highly successful in the ISM (2.4 GHz), the U-NII (5–6 GHz), and microwave (57–64 GHz) bands, by making the unused spectra accessible on an unlicensed basis. However, in order to obtain spectra for unlicensed operation, new sharing concepts have been introduced to allow the usage of spectra by secondary users under the prerequisite that they limit their interference to the primary users. This would start by studying techniques employed in the design of UWB filters. This study is aimed to investigate the filters for overlay and underlay CR. This paper presents a comparative study of ultra-wideband filters for Cognitive Radio Networks

A Fuzzy Interval Valued Fusion Technique for Multi- Modal 3D Face Recognition

Soodamani, R & Vimal, V (2016), Vehicle Detection for Traffic Flow Analysis, ICCST2016, Paper presented at the IEEE International Carnahan Conference on Security Technology, 24-27 October 2016, Orlando, Florida. This is the Accepted Manuscript version. The Version of Record is available online at IEEE Explore, doi: https://doi.org/10.1109/CCST.2016.7815709.This paper proposes a fuzzy interval valued multicriteria decision making (MCDM) technique that aggregates information from multi-modal feature sets during decision making in a 3D face recognition system. In this paper, an interval valued fuzzy TOPSIS technique is applied to a 3D face recognition system that is benchmarked against a set of databases. Such a system is shown to be useful in decision making when the choice of alternatives of the feature sets is combinatorial and complex.Final Accepted Versio

CLOUD COMPUTING IN AGRICULTURE – AN BOON

In India, around 75% of the population earns its livelihood from agriculture. It fulfills the basic need of human beings and animals. It is an important source of raw material for many agro-based industries. India’s geographical condition is unique for agriculture because it provides many favorable conditions. There are plain areas, fertile soil, long growing seasons, wide variation in climatic condition, etc. Apart from unique geographical conditions, India has been consistently making innovative efforts using science and technology to increase production. In that one the major booming sector is cloud computing, i.e., Cloud-agro revolution. Due to my passion in agriculture and tied to implement my research area in cloud. Today’s agriculture is embedded with advance services such as GPS and sensors [1] which is used to communicate with each other and also used to analyses and exchange Agri Information’s among them. IT provides services in the form of cloud to agriculture. Agri-cloud and IT offers expertise service to farmers regarding cultivation of crops, pricing, fertilizers, and diseases details and methods of cure to be used etc. In this field, there are huge discoveries, suggestions regarding modern techniques for cultivation, usage of fertilizers, can obtain cultivation history of the region, etc. In this paper, our study was based on is to design and implement a simple cloud-based application on Agriculture System which is based on agri-cloud that enhance agriculture production and also enhance the availability of data related to research projects in field

Fused LISS IV Image Classification using Deep Convolution Neural Networks

These days, earth observation frameworks give a large number of heterogeneous remote sensing information. The most effective method to oversee such fulsomeness in utilizing its reciprocity is a vital test in current remote sensing investigation. Considering optical Very High Spatial Resolution (VHSR) images, satellites acquire both Multi Spectral (MS) and panchromatic (PAN) images at various spatial goals. Information fusion procedures manage this by proposing a technique to consolidate reciprocity among the various information sensors. Classification of remote sensing image by Deep learning techniques using Convolutional Neural Networks (CNN) is increasing a solid decent footing because of promising outcomes. The most significant attribute of CNN-based strategies is that earlier element extraction is not required which prompts great speculation capacities. In this article, we are proposing a novel Deep learning based SMDTR-CNN (Same Model with Different Training Round with Convolution Neural Network) approach for classifying fused (LISS IV + PAN) image next to image fusion. The fusion of remote sensing images from CARTOSAT-1 (PAN image) and IRS P6 (LISS IV image) sensor is obtained by Quantization Index Modulation with Discrete Contourlet Transform (QIM-DCT). For enhancing the image fusion execution, we remove specific commotions utilizing Bayesian channel by Adaptive Type-2 Fuzzy System. The outcomes of the proposed procedures are evaluated with respect to precision, classification accuracy and kappa coefficient. The results revealed that SMDTR-CNN with Deep Learning got the best all-around precision and kappa coefficient. Likewise, the accuracy of each class of fused images in LISS IV + PAN dataset is improved by 2% and 5%, respectively