Wave attenuation and dispersion due to floating ice covers

Experiments investigating the attenuation and dispersion of surface waves in a variety of ice covers are performed using a refrigerated wave flume. The ice conditions tested in the experiments cover naturally occurring combinations of continuous, fragmented, pancake and grease ice. Attenuation rates are shown to be a function of ice thickness, wave frequency, and the general rigidity of the ice cover. Dispersion changes were minor except for large wavelength increases when continuous covers were tested. Results are verified and compared with existing literature to show the extended range of investigation in terms of incident wave frequency and ice conditions

Modeling and Sentiment Analysis of Online Reviews in Hospitality Industry

With the great extent of use of smartphones and the internet, the online hotel booking service providers have excessively increased thus producing more user-generated content in the form of reviews and comments about the customer experience. These reviews of visited customer’s aids hotel management personnel not only to forecast the future demand but also to implement effective strategies for better service. It is becoming a tuff job in this scenario for the hotel management to get exact information from the wide range of reviews. In this analysis, it is to identify the classification of the sentiment from the customer reviews. The classification can be done with text mining approach with the source of information. Two dictionaries are developed for the usage of data classification around 431 reviews taken from Tripadvisor.com and Booking.com. Finally Latent Dirichent Allocation (LDA) modeling algorithm is applied to identify related topics and it was used to sort out the issues in consumer sentiment analysis.     Study findings revealed that majority of the reviews were with positive sentiments and the topics found best with hospitality domain and sentiment term were such as “food”, “hospitality”, “room”, “people”, “friendly” , “Relax”, “feelings”, and “holiday” as hospitality terms and “Strong Positive” and “Ordinary Positive” as sentiment terms

The Lambert W Function and Quantum Statistics

We present some applications of the Lambert W function (W function) to the formalism of quantum statistics (QS). We consider the problem of finding extrema in terms of energy for a general QS distribution, which involves the solution of a transcendental equation in terms of the W function. We then present some applications of this formula including Bose–Einstein systems in d dimensions, Maxwell–Boltzmann systems, and black body radiation. We also show that for the appropriate parameter values, this formula reduces to an analytic expression in connection with Wien’s displacement law that was found in a previous study. In addition, we show that for Maxwell–Boltzmann and Bose–Einstein systems, the W function allows us to express the temperature of the system as a function of the thermodynamically relevant chemical potential, the particle density, and other parameters. Finally, we explore an indirect relationship of the W function to the polylogarithm function and to the Lambert transform

A quadratic boost converter derived multi output converter for electric vehicles application

A novel Solar Photo Voltaic Powered dual output DC to DC converter with the Quadratic Boost Converter as the core element, typically for Electrical Vehicle applications has been proposed and validated in this work. The proposed system harvests the solar power and charges a 12 V battery, supplies power to a 12 V load, using the buck feature of the proposed converter. A second channel of 48 V output is derived using the boost channel and the 48 V output is meant for driving the traction motor as well as any other load that requires a regulated 48 V. The proposed converter can operate in three different modes. For the purpose of voltage regulation at the 48 V and 12 V output channels and for the Maximum Power Point Tracking, applicable to the Solar Photo Voltaic source, individual Sliding Mode Controllers are used. The proposed idea has been validated using simulations in the MATLAB SIMULINK environment and an experimental prototype

Adaptive Optimized Discriminative Learning based Image Deblurring using Deep CNN

Image degradation plays a major problem in many image processing applications. Due to blurring, the quality of an image is degraded and there will be a reduction in bandwidth. Blur in an image is due to variations in atmospheric turbulence, focal length, camera settings, etc. Various types of blurs include Gaussian blur, Motion blur, Out-of-focus blur. The effect of noise along with blur further corrupts the captured image. Many techniques have evolved to deblur the degraded image. The leading approach to solve various degraded images are either based on discriminative learning models or on optimization models. Each method has its own advantages and disadvantages.  Learning by discriminative methods is faster but restricted to a specific task whereas optimization models handle flexibly but consume more time. Integrating optimization models suitably by learning with discriminative manner results in effective image restoration. In this paper, a set of effective and fast Convolutional Neural Networks (CNNs) are employed to deblur the Gaussian, motion and out-of-focus blurred images that integrate with optimization models to further avoid noise effects. The proposed methods work more efficiently for applications with low-level vision

Vacuum birefringence, the photon anomalous magnetic moment and the neutron star RX J1856.5−3754

We analyse the spectrum of the Hamiltonian of a photon propagating in a strong magnetic field B ∼ Bcr, where Bcr=m2e≃4.4×1013 role= presentation \u3eBcr=m2e≃4.4×1013 G is the Schwinger critical field. We show that the anomalous magnetic moment of a photon in the one-loop approximation is a non-decreasing function of the magnetic field B in the range 0 ≤ B ≤ 30 Bcr. We provide a numerical representation of the expression for the anomalous magnetic moment in terms of special functions. We find that the anomalous magnetic moment μγ of a photon for B = 30 Bcr is 8/3 of the anomalous magnetic moment of a photon for B = 1/2Bcr. Based on the recent observational evidence for vacuum birefringence from the neutron star RX J1856.5−3764 by Mignani et al., we suggest vacuum birefringence, the anomalous magnetic moment of the photon and the Faraday rotation angle as key observables for future experiments and measurements

VSI fed IM drive employing look-up tables with 6&12 sectors

Since the IM drives play a vital role for variable speed applications from fractional horse power to multi Mega-watt power, the control and estimation of induction motor drives constitute a vast subject. Nowadays, vector control and direct torque control (DTC) are popular for high performance drives. Even though these methods give better performance, the vector control method needs reference frame transformations and direct torque control gives large steady state ripples. To overcome these problems in the above methods mentioned, this paper presents an advanced vector control method for voltage-source inverter fed induction motors using sophisticated look-up tables. This method uses a predetermined look-up table instead of a much more time consuming pulse width modulation (PWM) procedure in conventional vector control for generating inverter gate signals. This approach gives faster torque response like in vector control methods and it also reduces ripples as in DTC method. To validate the proposed method numerical simulations have been carried out and compared with the existing algorithms. The simulation results confirm the effectiveness of the proposed method

Low latitude ionospheric response to March 2015 geomagnetic storm using multi-instrument TEC observations over India

The regional ionospheric models are successful in capturing the variability of ionosphere with the inclusion of local ground-based GPS observations and location dependent ionospheric dynamics. In this context, there is a need to develop regional ionospheric maps that aids in improving the consistency of global models. In this paper, an attempt is made to understand the potentiality of multi-instrument observations over Indian region. Four different Total Electron Content (TEC) data sources namely from network of GPS receivers, Ionosonde stations, space based COSMIC radio occultation profiles and SWARM mission data is utilized. The multi-source data is chosen for the geo-magnetic storm conditions prevailed during March 2015. Data from multiple-sources is observed over the period from 15th March 2015 to 20th March 2015. Validation of ground and space-based TEC data with International GNSS service (IGS) station data is significantly observed