Performance of a Low Heat Rejection Diesel Engine With Air Gap Insulated Piston

Introduction The second law requirement of Thermodynamics necessitates the inevitable heat loss to the coolant to realise work output. Any saving in this part of the energy distribution would either increase the energy lost through exhaust gases or increase the power output. Considerable efforts are under way to reduce heat loss to the coolant by various researchers. However, the results are a little confusing as to whether the insulation would improve or deteriorate thermal efficiency. The two approaches that are being pursued to decrease heat rejection are (1) ceramic coating and (2) air gap insulation. Both these methods are still having problems. Ceramic coatings are found to be peeling off over a period of operation. There are serious problems of leakage of gases in the case of air gap insulation. A two zone combustion model was used by A study of the existing literature on LHR engines thus reveal

Performance Analysis Of Adaptive Cross Layer FEC Mechanism For Video Transmission Over Wireless Networks

Abstract- The major challenges of video transmission over wireless networks is to have less error rate and to improve the quality of service. Many error control mechanisms are developed for video transmission on wireless networks. An Adaptive Cross-Layer FEC mechanism for Wireless Networks is used for video transmission which uses feedback to calculate the redundancy rate. The Cross-Layer FEC mechanism performs better in reducing error rate

ECG based Atrial Fibrillation detection using Sequency Ordered Complex Hadamard Transform and Hybrid Firefly Algorithm

Electrocardiogram (ECG), a non-invasive diagnostic technique, used for detecting cardiac arrhythmia. From last decade industry dealing with biomedical instrumentation and research, demanding an advancement in its ability to distinguish different cardiac arrhythmia. Atrial Fibrillation (AF) is an irregular rhythm of the human heart. During AF, the atrial moments are quicker than the normal rate. As blood is not completely ejected out of atria, chances for the formation of blood clots in atrium. These abnormalities in the heart can be identified by the changes in the morphology of the ECG. The first step in the detection of AF is preprocessing of ECG, which removes noise using filters. Feature extraction is the next key process in this research. Recent feature extraction methods, such as Auto Regressive (AR) modeling, Magnitude Squared Coherence (MSC) and Wavelet Coherence (WTC) using standard database (MIT-BIH), yielded a lot of features. Many of these features might be insignificant containing some redundant and non-discriminatory features that introduce computational burden and loss of performance. This paper presents fast Conjugate Symmetric Sequency Ordered Complex Hadamard Transform (CS-SCHT) for extracting relevant features from the ECG signal. The sparse matrix factorization method is used for developing fast and efficient CS-SCHT algorithm and its computational performance is examined and compared to that of the HT and NCHT. The applications of the CS-SCHT in the ECG-based AF detection is also discussed. These fast CS-SCHT features are optimized using Hybrid Firefly and Particle Swarm Optimization (FFPSO) to increase the performance of the classifier