The slot-coupled hemispherical dielectric resonator antenna with a parasitic patch: applications to the circularly polarized antenna and wide-band antenna

The aperture-coupled hemispherical dielectric resonator antenna (DRA) with a parasitic patch is studied rigorously. Using the Green's function approach, integral equations for the unknown patch and slot currents are formulated and solved using the method of moments. The theory is utilized to design a circularly polarized (CP) DRA and a wide-band linearly polarized (LP) DRA. In the former, the CP frequency and axial ratio (AR) can easily be controlled by the patch location and patch size, respectively, with the impedance matched by varying the slot length and microstrip stub length. It is important that the AR will not be affected when the input impedance is tuned, and the CP design is therefore greatly facilitated. For the wide-band LP antenna, a maximum bandwidth of 22% can be obtained, which is much wider than the previous bandwidth of 7.5% with no parasitic patches. Finally, the frequency-tuning characteristics of the proposed antenna are discussed. Since the parasitic patch can be applied to any DRAs, the method will find applications in practical DRA designs.     

A study of optimal viewing distance in a parallax barrier 3D display

The optimal viewing distance was proposed as a parameter for designing a parallax barrier 3D display. It can be designed based on simple geometric method and by considering the pitches of image display pixels and parallax barrier, or even including the aperture ratios of the image display pixels and parallax barrier. It can be analyzed by using ray tracing method. By considering the optical refraction index of the cover glass, the angular behavior of the system becomes more realistic; however, the geometric method is difficult to be used. We propose a revised method for estimating the view distance and angular behavior. In this paper, we have demonstrated a designated eye position (DEP) for each view and shown that multiple DEPs make a circular curve around the center of the display. We prove the new concept by comparing the optical ray tracing calculations and optical measurement.     

Modeling Default Data Via an Interactive Hidden Markov Model

In this paper, we first introduce the use of an interactive hidden Markov model (IHMM) for modeling and analyzing default data in a sector. Under the IHMM, transitions of the hidden risk states of the sector depend on the observed number of bonds in the sector that default in the current time period. This incorporates the feedback effect of the number of defaults on the transitions of the hidden risk states. This feature seems to be more realistic and does not enjoy by the traditional HMMs. We then develop a “dynamic” version of the binomial expansion technique (BET) modulated by the IHMM for modeling the occurrence of defaults of bonds issued by firms in the same sector. Under the BET modulated by the IHMM, the number of bonds defaulting in each time period follows a Markov-modulated binomial distribution with the probability of defaulting of each bond depending on the states of the IHMM, which represent the hidden risk states of the sector. Efficient method will be presented for estimating the model parameters in the BET modulated by the IHMM. We shall compare the hidden risk state process extracted from the IHMM-modulated BET with that extracted from the BET modulated by HMM in order to illustrate the significance of the feedback effect using real data. We shall also present the estimation results for the BET modulated by the IHMM and compare them with those for the BET modulated by the HMM.     

Control of discrete-time HMM partially observed under fractional Gaussian noises

A discrete-time control problem of a finite-state hidden Markov chain partially observed in a fractional Gaussian process is discussed using filtering. The control problem is then recast as a separated problem with information variables given by the unnormalized conditional probabilities of the whole path of the hidden Markov chain. A dynamic programming result and a minimum principle are obtained.     

A confidence-based framework for business to consumer (B2C) mobile commerce adoption

The Technology Acceptance Model (TAM) has been considered to be fundamental in determining the acceptance of new technology in the past decades. The two beliefs, ease of use and usefulness, in the model may not, however, fully explain the consumers’ behavior in an emerging environment, such as mobile commerce (m-commerce). This paper aims to develop a framework for m-commerce adoption in consumer decision-making processes. In this paper TAM has been adopted and extended to analyze successful m-commerce adoption. The key elements of the proposed confidence-based framework for B2C m-commerce adoption include psychological and behavioral factors. Psychological factors include history-based confidence, institution-based confidence and personality-based confidence. Behavioral factors include perceived ease of use and perceived usefulness of the mobile application and technology.     

Oscillation and convergence behaviours exhibited in an ‘unstable’ second‐order digital filter with saturation‐type non‐linearity

This letter explains the oscillatory behaviours exhibited in a second‐order digital filter with saturation‐type non‐linearity via the Hopf bifurcation theorem. It is shown that depending on the bifurcation parameter, the state variables may converge to zero even when the eigenvalues of the system matrix are outside the unit circle. Copyright © 2004 John Wiley & Sons, Ltd. abstract