Thermal Reactivity of Methylammonium Nitrates

The reactivity of the mono-, di- and trimethyl-ammonium nitrates to heat has been studied using differential thermal analysis, thermogravimetry and mass spectral analysis. The decomposition temperature of these compounds increases in the order CH₃NH₃NO₃ > (CH₃)₂NH₂NO₃ > (CH₃)₃NHNO₃. The activation energies have been determined employing isothermal decomposition technique. Mass spectrometric investigation shows that the extent of decomposition increases with increasing substitution on the nitrogen atom. Possible reasons for such behaviour have been explored.     

Mid-IR biosensor: detection and fingerprinting of pathogens on gold island functionalized chalcogenide films

Antibody (human IgG, anti-E. coli O157:H7, and anti-Salmonella) complexes on the surface of IR-transparent Ge-containing chalcogenide glass films were formed via thiol chemistry on 20-nm-thick gold islands. As a first step, the protocol was validated by monitoring fluorescently tagged targets to validate binding. FT-IR spectroscopy confirmed that the coating of the films with 20-nm gold did not have a significant effect on the propagation and penetration of IR evanescent waves through the film. The films functionalized with anti-E. coli O157:H7 and anti-Salmonella antibodies were used to detect E. coli O157:H7 and S. enteriditis through label-free IR fingerprinting. Highly selective detection of bacterial targets was achieved at both the species (E. coli vs. S. enteriditis) and strain level (E. coli O157:H7 vs E. coli K12). A mid-infrared approach could thus be used as a biosensor as well as a molecular fingerprinting tool.     

Medical Data Clustering and Classification Using TLBO and Machine Learning Algorithms

This study aims to empirically analyze teaching-learning-based optimization (TLBO) and machine learning algorithms using k-means and fuzzy c-means (FCM) algorithms for their individual performance evaluation in terms of clustering and classification. In the first phase, the clustering (k-means and FCM) algorithms were employed independently and the clustering accuracy was evaluated using different computational measures. During the second phase, the non-clustered data obtained from the first phase were preprocessed with TLBO. TLBO was performed using k-means (TLBO-KM) and FCM (TLBO-FCM) (TLBO-KM/FCM) algorithms. The objective function was determined by considering both minimization and maximization criteria. Non-clustered data obtained from the first phase were further utilized and fed as input for threshold optimization. Five benchmark datasets were considered from the University of California, Irvine (UCI) Machine Learning Repository for comparative study and experimentation. These are breast cancer Wisconsin (BCW), Pima Indians Diabetes, Heart-Statlog, Hepatitis, and Cleveland Heart Disease datasets. The combined average accuracy obtained collectively is approximately 99.4% in case of TLBO-KM and 98.6% in case of TLBO-FCM. This approach is also capable of finding the dominating attributes. The findings indicate that TLBO-KM/FCM, considering different computational measures, perform well on the non-clustered data where k-means and FCM, if employed independently, fail to provide significant results. Evaluating different feature sets, the TLBO-KM/FCM and SVM(GS) clearly outperformed all other classifiers in terms of sensitivity, specificity and accuracy. TLBO-KM/FCM attained the highest average sensitivity (98.7%), highest average specificity (98.4%) and highest average accuracy (99.4%) for 10-fold cross validation with different test data.     

Phasor-Domain Modeling of Resonant Inverters for High-Frequency AC Power Distribution Systems

The circuit modeling and analysis of resonant inverters is complex because the state variables such as inductor currents and capacitor voltages are AC dominant. The phasor dynamic modeling method maps the periodical time-varying state variables into stationary frame for each harmonic of interest. Correspondingly, the circuit is decomposed into two DC subcircuits, the state variables of which are the time-varying Fourier coefficients of the original AC variables. A small-signal model can be derived by applying small perturbation and linearization to the Fourier coefficients. A phasor-domain modeling method is used to investigate the resonant inverters in high-frequency AC power distribution systems. A resonant inverter system with five energy storage elements is modeled and simulated, and compared with switch simulation for both steady state and transients. The phasor model simulation matches the switch model simulation in both steady state and transients, but takes much less computing time. In addition, this model closely relates to the power converter topology in time domain, and therefore, keeps the physical meaning of the state variables. It can be used for high accuracy of modeling, simulation, and circuit analysis and control design. It can be extended to a higher order of resonant topologies including parasitic components. A high-frequency AC system with two pulse-phase-modulation-controlled resonant inverters is modeled and simulated, and the current distribution control is investigated with the phasor model. The model simulation is compared with switch-level simulation and experimental results.     

Simplified current minimization control of vector controlled Interior Permanent Magnet motor

This paper presents a simplified current minimizing technique for Interior Permanent Magnet (IPM) motor. This is primarily achieved by utilizing normalized 2D-Look Up Table (LUT) that is parameter independent except for saliency ratio. In addition, torque-flux reference frame is considered for implementation to reduce the complexity generally present in conventional methods utilizing i_ds ? i_qs current reference frame. The proposed algorithm also incorporates both the aspects that lead to field weakening operation, i.e., increase in speed and reduction of dc link voltage. A novel compensation method for incorporating saturation effect is also addressed. The current minimizing technique is analyzed in detail, supported by experimental results.     

Protocol design and resource allocation for power optimization using spectrum sharing for 5G networks

Telecommunication Systems - In this paper, we propose a spectrum sharing protocol wherein the sharing is performed in a situation without introducing a secondary transmitter in assisting the...     

Investigations for the optimal combination of zinc oxide nanoparticle-diesel fuel with optimal compression ratio for improving performance and reducing the emission features of variable compression ratio diesel engine

Clean Technologies and Environmental Policy - The continual hike in environmental pollution from diesel engines has raised the concern of researchers to identify certain clean fuels. For this...