Robust reweighted MAP motion estimation

This paper proposes a motion estimation algorithm that is robust to motion discontinuity and noise. The proposed algorithm is constructed by embedding the least median squares (LMedS) of robust statistics into the maximum a posteriori (MAP) estimator. Difficulties in accurate estimation of the motion field arise from the smoothness constraint and the sensitivity to noise. To cope robustly with these problems, a median operator and the concept of reweighted least squares (RLS) are applied to the MAP motion estimator, resulting in the reweighted robust MAP (RRMAP). The proposed RRMAP motion estimation algorithm is also generalized for multiple image frame cases. Computer simulation with various synthetic image sequences shows that the proposed algorithm reduces errors, compared to three existing robust motion estimation algorithms that are based on M-estimation, total least squares (TLS), and Hough transform. It is also observed that the proposed algorithm is statistically efficient and robust to additive Gaussian noise and impulse noise. Furthermore, the proposed algorithm yields reasonable performance for real image sequences     

Negotiation Agents that Make Prudent Compromises and are Slightly Flexible in Reaching Consensus

The contribution of this work is designing and developing enhanced market-driven agents with the flexibility to (1) respond to changing market conditions, and (2) raise and relax trade aspirations. Previous theoretical analyses have shown that market-driven agents ( MDA s) make prudent compromises by reacting to changing market situations by taking into account factors such as competition, deadlines, and trading options. This work augments the design of an MDA with three fuzzy decision controllers that guide the agent in (i) relaxing trade aspiration in face of intense negotiation pressure, and (ii) raising trade aspiration in extremely favorable markets. Results from extensive simulations conducted using an implemented testbed suggest that when compared to MDA s, agents in this work achieved (1) higher success rates in reaching deals, (2) higher average utilities, and (3) higher expected utility.     

Effect of shot noise and secondary emission noise in scanning electron microscope images

The effect of shot noise and emission noise due to materials that have different emission properties was simulated. Local variations in emission properties affect the overall signal‐to‐noise ratio (SNR) value of the scanning electron microscope image. In the case in which emission noise is assumed to be absent, the image SNRs for silicon and gold on a black background are identical. This is because only shot noise in the primary beam affects the SNRs, irrespective of the assumed noiseless secondary electron emission or backscattered electron emission processes. The addition of secondary emission noise degrades the SNR. Materials with higher secondary electron yield and backscattering electron yield give rise to higher SNR. For images formed from two types of material, the contrast of the image is lower. The reduction in image signal reduces the overall image SNR. As expected, large differences in δ or η give rise to higher SNR images.     

Autoregressive Wiener filtering in a scanning electron microscopy imaging system

In this paper, we propose to use the autoregressive (AR)-based interpolator with Wiener filter and apply the idea to scanning electron microscope (SEM) images. The concept for combining the AR-based interpolator with Wiener filtering comes from the essential requirement of Wiener filtering for accurate and consistent estimation of the power of the noise in images prior to filter implementation. The resultant filter is called AR-Wiener filter. The proposed filter is embedded onto the frame grabber card of the scanning electron microscope (SEM) for real-time image processing. Different images are captured using SEM and used to compare the performances of the conventional Wiener and the proposed AR-Wiener technique.     

Image signal-to-noise ratio estimation using Shape-Preserving Piecewise Cubic Hermite Autoregressive Moving Average model

We propose to cascade the Shape-Preserving Piecewise Cubic Hermite model with the Autoregressive Moving Average (ARMA) interpolator; we call this technique the Shape-Preserving Piecewise Cubic Hermite Autoregressive Moving Average (SP2CHARMA) model. In a few test cases involving different images, this model is found to deliver an optimum solution for signal to noise ratio (SNR) estimation problems under different noise environments. The performance of the proposed estimator is compared with two existing methods: the autoregressive-based and autoregressive moving average estimators. Being more robust with noise, the SP2CHARMA estimator has efficiency that is significantly greater than those of the two methods.     

Direct vapor phase growth process and robust photoluminescence properties of large area MoS2 layers

There has been growing research interest in the use of molybdenum disulfide in the fields of optoelectronics and energy harvesting devices, by virtue of its indirect-to-direct band gap tunability. However, obtaining large area thin films of MoS2 for future device applications still remains a challenge. In the present study, the amounts of the precursors （S and MOO3） were varied systematically in order to optimize the growth of highly crystalline and large area MoS2 layers by the chemical vapor deposition method. Careful control of the amounts of precursors was found to the key factor in the synthesis of large area highly crystalline flakes. The thickness of the layers was confirmed by Raman spectroscopy and atomic force microscopy. The optical properties and chemical composition were studied by photoluminescence （PL） and X-ray photoelectron spectroscopy. The emergence of strong direct excitonic emissions at 1.82 eV （A-exciton, with a normalized PL intensity of -55 × 10^3） and 1.98 eV （B-exciton, with a normalized PL intensity of -5 × 10^3） of the sample at room temperature clearly indicates the high luminescence quantum efficiency. The mobility of the films was found to be 0.09 cm^2/（V.s） at room temperature. This study provides a method for the controlled synthesis of high-quality two-dimensional （2D） transition metal dichalcogenide materials, useful for applications in nanodevices, optoelectronics and solar energv conversion.     

A uniplanar printed antenna with an inverted L‐shaped coupling feed for LTE/GSM/DCS/PCS/UMTS operations

A novel uniplanar printed antenna with a total size of 115 × 40 mm² is proposed for mobile device application. By using an inverted L‐shaped feeding mechanism and a meandered shorting strip, a dual‐band operation with wideband characteristic can be achieved. Here, the lower operating band is able to cover the LTE 700 and GSM 850/900 operations, while the higher operating band allows DCS 1800, PCS 1900, UMTS, and LTE 2300 operations. Furthermore, in order to increase the bandwidth of the higher operating band so that LTE 2500 operation can also be covered, an additional parasitic stub is attached to the feed line to excite a resonant frequency at around 2.72 GHz. Parametric studies via simulation are carried out, and prototype of the proposed antenna is also experimentally investigated to validate the simulated results. © 2012 Wiley Periodicals, Inc. Int J RF and Microwave CAE, 2012.     

CAR T Cell Therapy in Hematological Malignancies: Implications of the Tumor Microenvironment and Biomarkers on Efficacy and Toxicity

Chimeric antigen receptor (CAR) T cell therapy has ushered in a new era in cancer treatment. Remarkable outcomes have been demonstrated in patients with previously untreatable relapsed/refractory hematological malignancies. However, optimizing efficacy and reducing the risk of toxicities have posed major challenges, limiting the success of this therapy. The tumor microenvironment (TME) plays an important role in CAR T cell therapy’s effectiveness and the risk of toxicities. Increasing research studies have also identified various biomarkers that can predict its effectiveness and risk of toxicities. In this review, we discuss the various aspects of the TME and biomarkers that have been implicated thus far and discuss the role of creating scoring systems that can aid in further refining clinical applications of CAR T cell therapy and establishing a safe and efficacious personalised medicine for individuals.     

Face Detection: A Survey

In this paper we present a comprehensive and critical survey of face detection algorithms. Face detection is a necessary first-step in face recognition systems, with the purpose of localizing and extracting the face region from the background. It also has several applications in areas such as content-based image retrieval, video coding, video conferencing, crowd surveillance, and intelligent human–computer interfaces. However, it was not until recently that the face detection problem received considerable attention among researchers. The human face is a dynamic object and has a high degree of variability in its apperance, which makes face detection a difficult problem in computer vision. A wide variety of techniques have been proposed, ranging from simple edge-based algorithms to composite high-level approaches utilizing advanced pattern recognition methods. The algorithms presented in this paper are classified as either feature-based or image-based and are discussed in terms of their technical approach and performance. Due to the lack of standardized tests, we do not provide a comprehensive comparative evaluation, but in cases where results are reported on common datasets, comparisons are presented. We also give a presentation of some proposed applications and possible application areas.     

Reduction of flow-induced noise in a household air purifier

Journal of Mechanical Science and Technology - In this study, we propose a design for a household air purifier that reduces the flow-induced noise caused by the impeller of the fan system. The...