Slice sampling technique in Bayesian extreme of gold price modelling

In this paper, a simulation study of Bayesian extreme values by using Markov Chain Monte Carlo via slice sampling algorithm is implemented. We compared the accuracy of slice sampling with other methods for a Gumbel model. This study revealed that slice sampling algorithm offers more accurate and closer estimates with less RMSE than other methods. Finally we successfully employed this procedure to estimate the parameters of Malaysia extreme gold price from 2000 to 2011

Slice sampler algorithm for generalized pareto distribution

In this paper, we developed the slice sampler algorithm for the generalized Pareto distribution (GPD) model. Two simulation studies have shown the performance of the peaks over given threshold (POT) and GPD density function on various simulated data sets. The results were compared with another commonly used Markov chain Monte Carlo (MCMC) technique called Metropolis-Hastings algorithm. Based on the results, the slice sampler algorithm provides closer posterior mean values and shorter 95% quantile based credible intervals compared to the Metropolis-Hastings algorithm. Moreover, the slice sampler algorithm presents a higher level of stationarity in terms of the scale and shape parameters compared with the Metropolis-Hastings algorithm. Finally, the slice sampler algorithm was employed to estimate the re- turn and risk values of investment in Malaysian gold market

Strategy on implementing genetic algorithm on FPGA for polarization control application

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Enhancement of polarization controller characterization using genetic algorithm

We propose and demonstrate characterization of 8-stage LiNbO3 polarization controller (PC) by using Genetic Algorithm. An ability of GA to work efficiently in polarization control system possesses many advantages including easy code construction, consumption low memory and fast control speed. This algorithm is intelligent enough to characterize the PC accurately in 300 μs

Demonstration of duty cycle division multiplexing with bit error rate estimation

Experimental demonstration of Duty Cycle Division Multiplexing (DCDM) is reported which validates the potential implementation of the system in communication field. We also presented the operation of bit error rate (BER) estimation algorithm, which is specially derived for DCDM. With the increase of link attenuation, the signal amplitude decreased and the pulses are distorted. BER estimation on the received signal was performed and measured against transmission distance of 100 meter until 400 meter copper wire. It is shown that the channel with the largest duty-cycle value shows the best performance. The experimental eye diagrams at several distances are also demonstrated and compared against their back-to-back counterpart

Realization of microcontroller-based polarization control system with genetic algorithm

Realization of a PIC32 microcontroller-based polarization control system is described. Genetic algorithm is used for control purposes. The controller measures the signal intensity to estimate the genetic value. To reach optimum performance, the code is optimized by using the best genetic parameter to achieve the fastest execution time. This algorithm consumes low size of memory besides providing fast speed. The implementation of microcontroller allows for more economic polarization control solution

High gain of UWB planar antenna utilising FSS reflector for UWB applications

In this paper, a high gain and directional coplanar waveguide (CPW)- fed ultra-wideband (UWB) planar antenna with a new frequency selective surface (FSS) unit cells design is proposed for UWB applications. The proposed UWB antenna was designed based on the Mercedes artistic-shaped planar (MAP) antenna. The antenna consisted of a circular ring embedded with three straight legs for antenna impedance bandwidth improvement. The modelled FSS used the integration of a two parallel conductive metallic patch with a circular loop structure. The FSS provided a UWB stopband filter response covering a bandwidth of 10.5 GHz, for frequencies from 2.2 to 12.7 GHz. The proposed FSS had a compact physical dimension of 5 mm × 5 mm × 1.6 mm, with a printed array of 19 × 19 FSS unit cells. The FSS unit cells were printed on only one side of the dielectric FR4 substrate and placed as a sandwich between the antenna and the reflector ground plane. An equivalent circuit configuration (ECC) was used to verify the FSS unit cell structure’s performance. The simulated results indicated that the UWB MAP antenna and FSS reflector provided a fractional bandwidth of 136% and a high gain of 11.5 dB at 8.5 GHz with an acceptable radiation efficiency of 89%. Furthermore, the gain was improved across the operating band and kept between 8.3 and 11.5 dB. The proposed antenna was in good agreement between theoretical and experimental results and offered a wide enough bandwidth for UWB and vehicle applications

Tracking the early depleting transmission dynamics of COVID-19 with a time-varying SIR model

The susceptible-infectious-removed (SIR) model offers the simplest framework to study transmission dynamics of COVID-19, however, it does not factor in its early depleting trend observed during a lockdown. We modified the SIR model to specifically simulate the early depleting transmission dynamics of COVID-19 to better predict its temporal trend in Malaysia. The classical SIR model was fitted to observed total (I total), active (I) and removed (R) cases of COVID-19 before lockdown to estimate the basic reproduction number. Next, the model was modified with a partial time-varying force of infection, given by a proportionally depleting transmission coefficient, βt and a fractional term, z. The modified SIR model was then fitted to observed data over 6 weeks during the lockdown. Model fitting and projection were validated using the mean absolute percent error (MAPE). The transmission dynamics of COVID-19 was interrupted immediately by the lockdown. The modified SIR model projected the depleting temporal trends with lowest MAPE for I total, followed by I, I daily and R. During lockdown, the dynamics of COVID-19 depleted at a rate of 4.7% each day with a decreased capacity of 40%. For 7-day and 14-day projections, the modified SIR model accurately predicted I total, I and R. The depleting transmission dynamics for COVID-19 during lockdown can be accurately captured by time-varying SIR model. Projection generated based on observed data is useful for future planning and control of COVID-19

Public health and safety on close contact proximity detection for COVID-19 and alert via IoT

Social distancing among people is vital in minimizing spread of COVID-19 within community and can be effective in flattening the outbreak. This research work focuses on developing a close contact proximity detection system among smartphone users, particularly of COVID-19 patient, using Bluetooth signal to identify and analyze close contact proximity and social distancing from other anonymous smartphone user in their surrounding. The system aims to alert user if the social distancing is breached. The methodology rely on the Radio Signal Strength Indicator (RSSI) signal to analyze and estimate the proximity distance and duration of the individual’s exposure to other peoples in surrounding area. An overlap zone of 1-meter is used to indicate detection of closed contact proximity between users. Furthermore, the collected data can be utilized for contact tracing that enabling health officials to identify the closed contact of infected patient systematically and rapidly covering people who may be anonymous or not directly known to the COVID-19 patient. Encouraging results have been obtained for the closed contact proximity detection within the mobile apps. Furthermore, the performance of system for close contact proximity detection has shown that indoor locations have a more robust signal distribution compared to outdoor location