The wave packet transform in the framework of linear canonical transform

In this paper, we introduce the concept of linear canonical wave packet transform (LCWPT) based on the idea of linear canonical transform (LCT) and wave packet transform (WPT). Parseval’s identity and some properties of LCWPT are discussed. The inversion formula of LCWPT is formulated. Moreover, the composition of LCWPTs is defined and some properties are studied related to it. The LCWPTs of Mexican hat wavelet function are obtained.

Excellent Room-Temperature Thermoelectricity of 2D GeP3: Mexican-Hat-Shaped Band Dispersion and Ultralow Lattice Thermal Conductivity

Although some atomically thin 2D semiconductors have been found to possess good thermoelectric performance due to the quantum confinement effect, most of their behaviors occur at a higher temperature. Searching for promising thermoelectric materials at room temperature is meaningful and challenging. Inspired by the finding of moderate band gap and high carrier mobility in monolayer GeP3, we investigated the thermoelectric properties by using semi-classical Boltzmann transport theory and first-principles calculations. The results show that the room-temperature lattice thermal conductivity of monolayer GeP3 is only 0.43 Wm−1K−1 because of the low group velocity and the strong anharmonic phonon scattering resulting from the disordered phonon vibrations with out-of-plane and in-plane directions. Simultaneously, the Mexican-hat-shaped dispersion and the orbital degeneracy of the valence bands result in a large p-type power factor. Combining this superior power factor with the ultralow lattice thermal conductivity, a high p-type thermoelectric figure of merit of 3.33 is achieved with a moderate carrier concentration at 300 K. The present work highlights the potential applications of 2D GeP3 as an excellent room-temperature thermoelectric material.

Enviromental Pattern Analysis of Biodiesel (Castor, Coconut, MGB) to Support Alternative Energy using CFD approach

The Ship uses the MTU 16V956 TB 92 propulsion engine with a piston-type Mexican Hat combustion chamber. In general, the crown is used on machines with large torque. Besides that, the crown shape in the combustion chamber is also very influential on the formation of a mixture of fuel and air before the combustion process occurs. So it is necessary to know about the spray pattern of biodiesel fuel of enviromental things (castor, coconut, used cooking oil/MGB) in the Mexican Hat combustion chamber. In this study, using the Mexican Hat-shaped piston crown simulation method, the first step was to test the spray pattern of the three types of biodiesel (castor, coconut, used cooking oil) by simulating a tube with an injection pressure of 350 bar gauge pressure inside a barometric pressure tube. While the completion in the Mexican Hat combustion chamber with a chamber pressure of 35 bar gauge and injection pressure of 350 bar gauge was completed with the CFD program, Fluent 6.2, and the results of the three biodiesels were compared. From the CFD simulation results obtained spray patterns of the three types of biodiesel (castor, coconut, used cooking oil). At the same injection pressure and chamber pressure, used cooking biodiesel has the longest penetration length, followed by castor biodiesel and coconut biodiesel. The spray angle of coconut biodiesel is the largest, followed by castor biodiesel and used cooking oil biodiesel. SMD coconut biodiesel is the smallest, followed by castor biodiesel and used cooking oil biodiesel.

Nystagmus Estimation for Dizziness Diagnosis by Pupil Detection and Tracking Using Mexican-Hat-Type Ellipse Pattern Matching

The detection of nystagmus using video oculography experiences accuracy problems when patients who complain of dizziness have difficulty in fully opening their eyes. Pupil detection and tracking in this condition affect the accuracy of the nystagmus waveform. In this research, we design a pupil detection method using a pattern matching approach that approximates the pupil using a Mexican hat-type ellipse pattern, in order to deal with the aforementioned problem. We evaluate the performance of the proposed method, in comparison with that of a conventional Hough transform method, for eye movement videos retrieved from Gifu University Hospital. The performance results show that the proposed method can detect and track the pupil position, even when only 20% of the pupil is visible. In comparison, the conventional Hough transform only indicates good performance when 90% of the pupil is visible. We also evaluate the proposed method using the Labelled Pupil in the Wild (LPW) data set. The results show that the proposed method has an accuracy of 1.47, as evaluated using the Mean Square Error (MSE), which is much lower than that of the conventional Hough transform method, with an MSE of 9.53. We conduct expert validation by consulting three medical specialists regarding the nystagmus waveform. The medical specialists agreed that the waveform can be evaluated clinically, without contradicting their diagnoses.