Harrison’s Stolen: Addressing Aboriginal and Indigenous Islanders Human Rights

According to the United Nations Declaration of Human Rights in 1948, every human being is entitled to rights in life that should be respected by others and protected by the state and community. Such rights are inherent regardless of colour, ethnicity, gender, religion or otherwise, and it is expected that all humans alike have the right to live without discrimination of any sort. However, that has not been the case with Aborigines in Australia. Over a long period of time, the governments of the State and the Territories and the Australian Commonwealth denied the Aboriginal and Indigenous inhabitants of the Torres Strait Islands such rights. Past Australian governments set policies and laws that enabled them to forcefully remove Indigenous children from their parents, which resulted in creating lost generations living the trauma of the loss of cultural identity, alienation and even their own selfhood. Intending to reduce that population of natives and their Aboriginal culture while, on the other hand, assimilate them into mainstream society, they gave themselves the right to remove them from their families with no hope of return. That practice has led to tragic consequences due to the trauma that has affected those children, an experience that is depicted by Jane Harrison in her play Stolen. The drama is the outcome of a six-year project on lost children and which was first performed in 1997 in Melbourne. Five actors only appear on the stage, playing the role of all the different characters, whether the main protagonists or the remaining cast, present or non-present ones as voices. The play outlines the life of five children who have been taken from their parents at an early age, entailing a disastrous negative impact that differs from one to the other. Unknown to each other, what connects between them is being put in a children’s home. The purpose of this paper is to analyse the play’s text in light of the 1948 Declaration of Human Rights, using it as a lens that reflects the atrocities practiced against the Aborigines. It highlights how such practices formed an outrageous violation of those natives’ rights as human beings. Harrison’s dramatic technique in conveying the children’s experiences is through a non-linear structure, fluctuating between past and present that are linked together within each of the five characters, reflecting their suffering and pain to create an emotional link between them and the audience. Her dramatic handling of the issue by fusing tragedy with humour as well as symbolism is a successful technique in revealing the traumatic memory of those children and their present life. The play has made a difference in commencing to address the problem of the right of all children to be with their families, which renders the real meaning of having a home and an identity as people.

MHD Natural Convection Flow of Tangent Hyperbolic Nanofluid Past a Vertical Permeable Cone

In this paper, a non-similraity analysis has been presented to exhibit the two-dimensional boundary layer flow of magnetohydrodynamic (MHD) natural convection of tangent hyperbolic nanofluid nearby a vertical permeable cone in the presence of variable wall temperature impact. The mutated boundary layer nonlinear governing equations are solved numerically by the an efficient implicit finite difference procedure. For both nanofluid effective viscosity and nanofluid thermal conductivity, a number of experimental relations have been recognized. For characterizing the nanofluid, the compatible nanoparticle volume fraction model has been used. Nusselt number and skin friction coefficient are calculated for some values of Weissenberg number W, surface temperature exponent n, magnetic field parameter Mg, power law index m and Prandtl number Pr as functions of suction parameter. The rate of heat transfer from a vertical permeable cone in a regular fluid is less than that in nanofluids. A best convection has been presented by Copper nanoparticle among all the used nanoparticles.

Residual Modulus of Elasticity of Self-Compacting Concrete Incorporated Unprocessed Waste Fly Ash after Expose to the Elevated Temperature

The present study experimentally investigated the impact of incorporating unprocessed waste fly ash (UWFA) on the residual mechanical properties of self-compacting concrete (SCC) after exposure to elevated temperature. Three mixtures of SCC have been produced by replacing the cement mass by 0%, 15% and 30% of UWFA. Generally, the fire resistance of SCC has been enhanced by replacing the cement up to 15% of UWFA, especially in case of residual modulus of elasticity which considers more sensitive than other mechanical properties at elevated temperature. However, a strong linear relationship has been observed between the residual flexural strength and modulus of elasticity, where both of them affected significantly by the cracks appearance and propagation as a result of elevated temperature. Sustainable products could be produced by incorporating unprocessed waste powder materials in the production of concrete, where the waste materials, CO2 emissions, and the energy needed for processing are reduced.

Pressure-Detecting Method for Estimating Levitation Gap Height of Swirl Gripper

The swirl gripper is an electrically activated noncontact handling device that uses swirling airflow to generate a lifting force. This force can be used to pick up a workpiece placed underneath the swirl gripper without any contact. It is applicable, for example, in the semiconductor wafer production line, where contact must be avoided during the handling and moving of a workpiece to minimize damage. When a workpiece levitates underneath a swirl gripper, the gap height between them is crucial for safe handling. Therefore, in this paper, we propose a method to estimate the levitation gap height by detecting pressure at two points. The method is based on theoretical model of the swirl gripper, and has been experimentally verified. Furthermore, the force between the gripper and the workpiece can also be estimated using the detected pressure. As a result, the nonlinear relationship between the force and gap height can be linearized by adjusting the rotating speed of the fan in the swirl gripper according to the estimated force and gap height. The linearized relationship is expected to enhance handling stability of the workpiece.

Linear Quadratic Gaussian/Loop Transfer Recover Control Flight Control on a Nonlinear Model

As part of the development of a 4D autopilot system for unmanned aerial vehicles (UAVs), i.e. a time-dependent robust trajectory generation and control algorithm, this work addresses the problem of optimal path control based on the flight sensors data output that may be unreliable due to noise on data acquisition and/or transmission under certain circumstances. Although several filtering methods, such as the Kalman-Bucy filter or the Linear Quadratic Gaussian/Loop Transfer Recover Control (LQG/LTR), are available, the utter complexity of the control system, together with the robustness and reliability required of such a system on a UAV for airworthiness certifiable autonomous flight, required the development of a proper robust filter for a nonlinear system, as a way of further mitigate errors propagation to the control system and improve its ,performance. As such, a nonlinear algorithm based upon the LQG/LTR, is validated through computational simulation testing, is proposed on this paper.

Optimizing Network Latency with Fast Path Assignment for Incoming Flows

Various flows in the network require to go through different types of middlebox. The improper placement of network middlebox and path assignment for flows could greatly increase the network latency and also decrease the performance of network. Minimizing the total end to end latency of all the ows requires to assign path for the incoming flows. In this paper, the flow path assignment problem in regard to the placement of various kinds of middlebox is studied. The flow path assignment problem is formulated to a linear programming problem, which is very time consuming. On the other hand, a naive greedy algorithm is studied. Which is very fast but causes much more latency than the linear programming algorithm. At last, the paper presents a heuristic algorithm named FPA, which takes bottleneck link information and estimated bandwidth occupancy into consideration, and achieves near optimal latency in much less time. Evaluation results validate the effectiveness of the proposed algorithm.

Fast and Efficient Algorithms for Evaluating Uniform and Nonuniform Lagrange and Newton Curves

Newton-Lagrange Interpolations are widely used in numerical analysis. However, it requires a quadratic computational time for their constructions. In computer aided geometric design (CAGD), there are some polynomial curves: Wang-Ball, DP and Dejdumrong curves, which have linear time complexity algorithms. Thus, the computational time for Newton-Lagrange Interpolations can be reduced by applying the algorithms of Wang-Ball, DP and Dejdumrong curves. In order to use Wang-Ball, DP and Dejdumrong algorithms, first, it is necessary to convert Newton-Lagrange polynomials into Wang-Ball, DP or Dejdumrong polynomials. In this work, the algorithms for converting from both uniform and non-uniform Newton-Lagrange polynomials into Wang-Ball, DP and Dejdumrong polynomials are investigated. Thus, the computational time for representing Newton-Lagrange polynomials can be reduced into linear complexity. In addition, the other utilizations of using CAGD curves to modify the Newton-Lagrange curves can be taken.

Low-Level Modeling for Optimal Train Routing and Scheduling in Busy Railway Stations

This paper studies a train routing and scheduling problem for busy railway stations. Our objective is to allow trains to be routed in dense areas that are reaching saturation. Unlike traditional methods that allocate all resources to setup a route for a train and until the route is freed, our work focuses on the use of resources as trains progress through the railway node. This technique allows a larger number of trains to be routed simultaneously in a railway node and thus reduces their current saturation. To deal with this problem, this study proposes an abstract model and a mixed-integer linear programming formulation to solve it. The applicability of our method is illustrated on a didactic example.

Electromagnetic Wave Propagation Equations in 2D by Finite Difference Method

In this paper, the techniques to solve time dependent electromagnetic wave propagation equations based on the Finite Difference Method (FDM) are proposed by comparing the results with Finite Element Method (FEM) in 2D while discussing some special simulation examples.  Here, 2D dynamical wave equations for lossy media, even with a constant source, are discussed for establishing symbolic manipulation of wave propagation problems. The main objective of this contribution is to introduce a comparative study of two suitable numerical methods and to show that both methods can be applied effectively and efficiently to all types of wave propagation problems, both linear and nonlinear cases, by using symbolic computation. However, the results show that the FDM is more appropriate for solving the nonlinear cases in the symbolic solution. Furthermore, some specific complex domain examples of the comparison of electromagnetic waves equations are considered. Calculations are performed through Mathematica software by making some useful contribution to the programme and leveraging symbolic evaluations of FEM and FDM.

Study of Structural and Electronic Properties of Ternary PdMnGe Half-Heusler Alloy

This study deals with the structural and electronic properties of ternary PdMnGe Half-Heusler alloy using the full potential linearized augmented plane wave (FP-LAPW) method based on the density functional theory (DFT) as implemented in the WIEN2k package, within the framework of generalized gradient approximation (GGA). Structural parameters, total and partial densities of states were also analyzed. The obtained result shows that the studied material is metallic in GGA treatment. The elastic constants (Cij) show that our compound is ductile, stiff and anisotropic.

Thermo-Mechanical Approach to Evaluate Softening Behavior of Polystyrene: Validation and Modeling

A Thermo-mechanical technique was developed to determine softening point temperature/glass transition temperature (Tg) of polystyrene exposed to high pressures. The design utilizes the ability of carbon dioxide to lower the glass transition temperature of polymers and acts as plasticizer. In this apparatus, the sorption of carbon dioxide to induce softening of polymers as a function of temperature/pressure is performed and the extent of softening is measured in three-point-flexural-bending mode. The polymer strip was placed in the cell in contact with the linear variable differential transformer (LVDT). CO2 was pumped into the cell from a supply cylinder to reach high pressure. The results clearly showed that full softening point of the samples, accompanied by a large deformation on the polymer strip. The deflection curves are initially relatively flat and then undergo a dramatic increase as the temperature is elevated. It was found that increasing the pressure of CO2 causes the temperature curves to shift from higher to lower by increment of about 45 K, over the pressure range of 0-120 bars. The obtained experimental Tg values were validated with the values reported in the literature. Finally, it is concluded that the defection model fits consistently to the generated experimental results, which attempts to describe in more detail how the central deflection of a thin polymer strip affected by the CO2 diffusions in the polymeric samples.

Classification Based on Deep Neural Cellular Automata Model

Deep learning structure is a branch of machine learning science and greet achievement in research and applications. Cellular neural networks are regarded as array of nonlinear analog processors called cells connected in a way allowing parallel computations. The paper discusses how to use deep learning structure for representing neural cellular automata model. The proposed learning technique in cellular automata model will be examined from structure of deep learning. A deep automata neural cellular system modifies each neuron based on the behavior of the individual and its decision as a result of multi-level deep structure learning. The paper will present the architecture of the model and the results of simulation of approach are given. Results from the implementation enrich deep neural cellular automata system and shed a light on concept formulation of the model and the learning in it.

Remaining Useful Life Estimation of Bearings Based on Nonlinear Dimensional Reduction Combined with Timing Signals

In data-driven prognostic methods, the prediction accuracy of the estimation for remaining useful life of bearings mainly depends on the performance of health indicators, which are usually fused some statistical features extracted from vibrating signals. However, the existing health indicators have the following two drawbacks: (1) The differnet ranges of the statistical features have the different contributions to construct the health indicators, the expert knowledge is required to extract the features. (2) When convolutional neural networks are utilized to tackle time-frequency features of signals, the time-series of signals are not considered. To overcome these drawbacks, in this study, the method combining convolutional neural network with gated recurrent unit is proposed to extract the time-frequency image features. The extracted features are utilized to construct health indicator and predict remaining useful life of bearings. First, original signals are converted into time-frequency images by using continuous wavelet transform so as to form the original feature sets. Second, with convolutional and pooling layers of convolutional neural networks, the most sensitive features of time-frequency images are selected from the original feature sets. Finally, these selected features are fed into the gated recurrent unit to construct the health indicator. The results state that the proposed method shows the enhance performance than the related studies which have used the same bearing dataset provided by PRONOSTIA.

The Association between Affective States and Sexual/Health-Related Status among Men Who Have Sex with Men in China: An Exploration Study Using Social Media Data

Objectives: The purpose of this study was to understand and examine the association between diurnal mood variation and sexual/health-related status among men who have sex with men (MSM) using data from MSM Chinese Twitter messages. The study consists of 843,745 postings of 377,610 MSM users located in Guangdong that were culled from the MSM Chinese Twitter App. Positive affect, negative affect, sexual related behaviors, and health-related status were measured using the Simplified Chinese Linguistic Inquiry and Word Count. Emotions, including joy, sadness, anger, fear, and disgust were measured using the Weibo Basic Mood Lexicon. A positive sentiment score and a positive emotions score were also calculated. Linear regression models based on a permutation test were used to assess associations between affective states and sexual/health-related status. In the results, 5,871 active MSM users and their 477,374 postings were finally selected. MSM expressed positive affect and joy at 8 a.m. and expressed negative affect and negative emotions between 2 a.m. and 4 a.m. In addition, 25.1% of negative postings were directly related to health and 13.4% reported seeking social support during that sensitive period. MSM who were senior, educated, overweight or obese, self-identified as performing a versatile sex role, and with less followers, more followers, and less chat groups mainly expressed more negative affect and negative emotions. MSM who talked more about sexual-related behaviors had a higher positive sentiment score (β=0.29, p < 0.001) and a higher positive emotions score (β = 0.16, p < 0.001). MSM who reported more on their health status had a lower positive sentiment score (β = -0.83, p < 0.001) and a lower positive emotions score (β = -0.37, p < 0.001). The study concluded that psychological intervention based on an app for MSM should be conducted, as it may improve mental health.

A Data Driven Approach for the Degradation of a Lithium-Ion Battery Based on Accelerated Life Test

Lithium ion batteries are currently used for many applications including satellites, electric vehicles and mobile electronics. Their ability to store relatively large amount of energy in a limited space make them most appropriate for critical applications. Evaluation of the life of these batteries and their reliability becomes crucial to the systems they support. Reliability of Li-Ion batteries has been mainly considered based on its lifetime. However, another important factor that can be considered critical in many applications such as in electric vehicles is the cycle duration. The present work presents the results of an experimental investigation on the degradation behavior of a Laptop Li-ion battery (type TKV2V) and the effect of applied load on the battery cycle time. The reliability was evaluated using an accelerated life test. Least squares linear regression with median rank estimation was used to estimate the Weibull distribution parameters needed for the reliability functions estimation. The probability density function, failure rate and reliability function under each of the applied loads were evaluated and compared. An inverse power model is introduced that can predict cycle time at any stress level given.

Pilot-Assisted Direct-Current Biased Optical Orthogonal Frequency Division Multiplexing Visible Light Communication System

Visible light communication (VLC) is a new approach of optical wireless communication proposed to support the congested radio frequency (RF) spectrum. VLC systems are combined with orthogonal frequency division multiplexing (OFDM) to achieve high rate transmission and high spectral efficiency. In this paper, we investigate the Pilot-Assisted Channel Estimation for DC biased Optical OFDM (PACE-DCO-OFDM) systems to reduce the effects of the distortion on the transmitted signal. Least-square (LS) and linear minimum mean-squared error (LMMSE) estimators are implemented in MATLAB/Simulink to enhance the bit-error-rate (BER) of PACE-DCO-OFDM. Results show that DCO-OFDM system based on PACE scheme has achieved better BER performance compared to conventional system without pilot assisted channel estimation. Simulation results show that the proposed PACE-DCO-OFDM based on LMMSE algorithm can more accurately estimate the channel and achieves better BER performance when compared to the LS based PACE-DCO-OFDM and the traditional system without PACE. For the same signal to noise ratio (SNR) of 25 dB, the achieved BER is about 5×10-4 for LMMSE-PACE and 4.2×10-3 with LS-PACE while it is about 2×10-1 for system without PACE scheme.

Magnetohydrodynamic Maxwell Nanofluids Flow over a Stretching Surface through a Porous Medium: Effects of Non-Linear Thermal Radiation, Convective Boundary Conditions and Heat Generation/Absorption

In this paper, an enhancement of the heat transfer using non-Newtonian nanofluids by magnetohydrodynamic (MHD) mixed convection along stretching sheets embedded in an isotropic porous medium is investigated. Case of the Maxwell nanofluids is studied using the two phase mathematical model of nanofluids and the Darcy model is applied for the porous medium. Important effects are taken into account, namely, non-linear thermal radiation, convective boundary conditions, electromagnetic force and presence of the heat source/sink. Suitable similarity transformations are used to convert the governing equations to a system of ordinary differential equations then it is solved numerically using a fourth order Runge-Kutta method with shooting technique. The main results of the study revealed that the velocity profiles are decreasing functions of the Darcy number, the Deborah number and the magnetic field parameter. Also, the increase in the non-linear radiation parameters causes an enhancement in the local Nusselt number.

Stress Analysis of Hexagonal Element for Precast Concrete Pavements

While the use of cast-in-place concrete for an airfield and highway pavement overlay is very common, the application of precast concrete elements is very limited today. The main reasons consist of high production costs and complex structural behavior. Despite that, several precast concrete systems have been developed and tested with the aim to provide a system with rapid construction. The contribution deals with the reinforcement design of a hexagonal element developed for a proposed airfield pavement system. The sub-base course of the system is composed of compacted recycled concrete aggregates and fiber reinforced concrete with recycled aggregates place on top of it. The selected element belongs to a group of precast concrete elements which are being considered for the construction of a surface course. Both high costs of full-scale experiments and the need to investigate various elements force to simulate their behavior in a numerical analysis software by using finite element method instead of performing expensive experiments. The simulation of the selected element was conducted on a nonlinear model in order to obtain such results which could fully compensate results from experiments. The main objective was to design reinforcement of the precast concrete element subject to quasi-static loading from airplanes with respect to geometrical imperfections, manufacturing imperfections, tensile stress in reinforcement, compressive stress in concrete and crack width. The obtained findings demonstrate that the position and the presence of imperfection in a pavement highly affect the stress distribution in the precast concrete element. The precast concrete element should be heavily reinforced to fulfill all the demands. Using under-reinforced concrete elements would lead to the formation of wide cracks and cracks permanently open.

An Improved Adaptive Dot-Shape Beamforming Algorithm Research on Frequency Diverse Array

Frequency diverse array (FDA) beamforming is a technology developed in recent years, and its antenna pattern has a unique angle-distance-dependent characteristic. However, the beam is always required to have strong concentration, high resolution and low sidelobe level to form the point-to-point interference in the concentrated set. In order to eliminate the angle-distance coupling of the traditional FDA and to make the beam energy more concentrated, this paper adopts a multi-carrier FDA structure based on proposed power exponential frequency offset to improve the array structure and frequency offset of the traditional FDA. The simulation results show that the beam pattern of the array can form a dot-shape beam with more concentrated energy, and its resolution and sidelobe level performance are improved. However, the covariance matrix of the signal in the traditional adaptive beamforming algorithm is estimated by the finite-time snapshot data. When the number of snapshots is limited, the algorithm has an underestimation problem, which leads to the estimation error of the covariance matrix to cause beam distortion, so that the output pattern cannot form a dot-shape beam. And it also has main lobe deviation and high sidelobe level problems in the case of limited snapshot. Aiming at these problems, an adaptive beamforming technique based on exponential correction for multi-carrier FDA is proposed to improve beamforming robustness. The steps are as follows: first, the beamforming of the multi-carrier FDA is formed under linear constrained minimum variance (LCMV) criteria. Then the eigenvalue decomposition of the covariance matrix is ​​performed to obtain the diagonal matrix composed of the interference subspace, the noise subspace and the corresponding eigenvalues. Finally, the correction index is introduced to exponentially correct the small eigenvalues ​​of the noise subspace, improve the divergence of small eigenvalues ​​in the noise subspace, and improve the performance of beamforming. The theoretical analysis and simulation results show that the proposed algorithm can make the multi-carrier FDA form a dot-shape beam at limited snapshots, reduce the sidelobe level, improve the robustness of beamforming, and have better performance.

Monte Carlo Estimation of Heteroscedasticity and Periodicity Effects in a Panel Data Regression Model

This research attempts to investigate the effects of heteroscedasticity and periodicity in a Panel Data Regression Model (PDRM) by extending previous works on balanced panel data estimation within the context of fitting PDRM for Banks audit fee. The estimation of such model was achieved through the derivation of Joint Lagrange Multiplier (LM) test for homoscedasticity and zero-serial correlation, a conditional LM test for zero serial correlation given heteroscedasticity of varying degrees as well as conditional LM test for homoscedasticity given first order positive serial correlation via a two-way error component model. Monte Carlo simulations were carried out for 81 different variations, of which its design assumed a uniform distribution under a linear heteroscedasticity function. Each of the variation was iterated 1000 times and the assessment of the three estimators considered are based on Variance, Absolute bias (ABIAS), Mean square error (MSE) and the Root Mean Square (RMSE) of parameters estimates. Eighteen different models at different specified conditions were fitted, and the best-fitted model is that of within estimator when heteroscedasticity is severe at either zero or positive serial correlation value. LM test results showed that the tests have good size and power as all the three tests are significant at 5% for the specified linear form of heteroscedasticity function which established the facts that Banks operations are severely heteroscedastic in nature with little or no periodicity effects.