Song Y.,Harbin Medical University |
Prakash R.,M S Ramaiah Medical College |
Reddy J.,Christ University
Neurology India | Year: 2016
Prediction of prognosis in comatose patients surviving a cardiac arrest is still one of the intractable problems in critical care neurology because of lack of fool-proof ways to assess the outcome. Of all these measures, somatosensory-evoked potential (SSEP) has been perhaps the most evaluated and heavily relied-upon tool over the past several decades for assessing coma. Recent studies have given rise to concerns regarding the 'absoluteness' of SSEP signals for the prognostic evaluation of coma. In this critical review, we searched the literature to focus on studies conducted so far on the prognostic evaluation of postanoxic coma using SSEPs. All those studies published on the use of SSEP as a prognostication tool in postanoxic coma were reviewed. A narrative review was created that included the strengths as well as limitations of the use of SSEP in postanoxic coma. The use of SSEP in coma has been universal for the purpose of prognostication. However, it has its own advantages as well as limitations. The limitations include challenges in performing and getting SSEP signals during coma as well as the challenges involved in reading and interpreting the signals. The recent usage of therapeutic hypothermia has become another factor that often interferes with the SSEP recording. Finally, based on these study results, some recommendations are generated for the effective use of SSEPs in comatose patients for further prognostication. We advocate that SSEP should be an integral component for the assessment of postanoxic comatose patients due to its several advantages over other assessment tools. However, SSEP recorDings should follow certain standards. One should be aware that its interpretation may be biased by several factors. The bias created by the concept of 'self-fulfilling hypothesis' should always be borne in mind before discontinuation of life support systems in terminal patients.
Balachandran K.,Christ University |
Anitha R.,KS Rangasamy College of Technology
Journal of Theoretical and Applied Information Technology | Year: 2013
World Health Organization (WHO) reports that worldwide 7.6 million deaths are caused by cancer each year. Uncontrollable cell development in the tissues of the lung is called as lung cancer. These uncontrollable cells restrict the growth of healthy lung tissues. If not treated, this growth can spread beyond the lung in the nearby tissue called metastasis and, form tumors. In order to preserve the life of the people who are suffered by the lung cancer disease, it should be pre-diagonized. So there is a need of pre diagnosis system for lung cancer disease which should provide better results. The proposed lung cancer prediagnosis technique is the combination of FFBNN and ABC. By using the Artificial Bee Colony (ABC) algorithm, the dimensionality of the dataset is reduced in order to reduce the computation complexity. Then the risk factors and the symptoms from the dimensional reduced dataset are given to the FFBNN to accomplish the training process. In order to get higher accuracy in the prediagnosis process, the FFBNN parameters are optimized using ABC algorithm. In the testing process, more data are given to well trained FFBNN-ABC to validate whether the given testing data predict the lung disease perfectly or not. © 2005-2013 JATIT & LLS.All rights reserved.
Daniel R.S.,Trichy Engineering College |
Suganthi S.,Christ University
ICIIECS 2015 - 2015 IEEE International Conference on Innovations in Information, Embedded and Communication Systems | Year: 2015
The aim of the paper is to design, and simulate circular spike Coplanar Waveguide (CPW) fed antenna for wireless applications. The size of the antenna is very small occupying a space of 36mm × 36mm including the substrate board. The antenna is designed using FR-4 substrate of thickness 1.6mm with dielectric permittivity of 4.4. The Coplanar Waveguide (CPW) fed system is used, so we can avoid double side printed board. This proposed antenna covers the bandwidth frequency range from 2.85GHz to 3.31GHZ and 5.09GHz to 5.65GHz for various wireless applications. The antenna design and performance are analyzed by using High Frequency Structure Simulator (HFSS) electromagnetic software for wireless applications according to frequency bands. The results of proposed antenna simulation on return loss, VSWR, gain and directivity are calculated. © 2015 IEEE.
Kumar Chandar S.,Christ University |
Kumar Chandar S.,Madurai Kamaraj University |
Sumathi M.,Sri Meenakshi Government College for Arts for Women Autonomous |
Sivanandam S.N.,Karpagam College of Engineering
International Journal of Engineering and Technology | Year: 2015
Foreign exchange market is the largest and the most important one in the world. Foreign exchange transaction is the simultaneous selling of one currency and buying of another currency. It is essential for currency trading in the international market. In this paper, we have investigated Artificial Neural Networks based prediction modelling of foreign exchange rates using five different training algorithms. The model was trained using historical data to predict four foreign currency exchange rates against Indian Rupee. The forecasting performance of the proposed system is evaluated by using statistical metric and compared. From the results, it is confirmed that the new approach provided an improve technique to forecast foreign exchange rate. It is also an effective tool and significantly close prediction can be made using simple structure. Among the five models, Levenberg-Marquardt based model outperforms than other models and attains comparable results. It also demonstrates the power of the proposed approach and produces more accurate prediction. In conclusion, the proposed scheme can improve the forecasting performance significantly when measured on three commonly used metrics.
Ajayakumar C.J.,Christ University |
Kunjomana A.G.,Christ University
Journal of Materials Science: Materials in Electronics | Year: 2016
Homogeneous and stoichiometric samples of InBi1−xSbx (x = 0, 0.1) crystals have been directionally solidified to explore their suitability for optoelectronic applications. Prior to the growth, the temperature distribution of an indigenously fabricated horizontal furnace has been analysed and optimized to conduct the growth experiments on the basis of phase diagram of the material. Systematic trials have been carried out for several growth runs (48, 60 and 72 h) by maintaining an axial temperature gradient of 4, 6 and 8 °C/cm with the aid of a temperature controller mechanism. The key parameters governing the growth mechanism, composition, phase, and structure of the grown InBi1−xSbx crystals were investigated via X-ray diffraction, scanning electron and atomic force microscopy, Raman and Fourier transform infrared spectroscopy. The presence of secondary phases was ruled out and the average congruent melting points of InBi and InBi0.9Sb0.1 samples were confirmed as 109.43 and 121.13 °C respectively, by employing differential scanning calorimetric analysis. Investigations on the optical, electrical and mechanical properties of these materials were carried out. Vickers microhardness was found to increase with the Sb incorporation. The average optical band gap computed from the IR transmission spectra was found to be 0.165 eV. The results obtained promise that InBi1−xSbx crystals grown by directional solidification are favourable candidates than those grown by other melt methods. © 2016 Springer Science+Business Media New York