At the National Synchrotron Radiation Research Center, a small/wide‐angle X‐ray scattering (SAXS/WAXS) instrument has been installed at the BL23A beamline with a superconducting wiggler insertion device. This beamline is equipped with double Si(111) crystal and double Mo/B4C multilayer monochromators, and an Si‐based plane mirror that can selectively deflect the beam downwards for grazing‐incidence SAXS (GISAXS) studies of air–liquid or liquid–liquid interfaces. The SAXS/WAXS instrument, situated in an experimental hutch, comprises collimation, sample and post‐sample stages. Pinholes and slits have been incorporated into the beam collimation system spanning a distance of ∼5 m. The sample stage can accommodate various sample geometries for air–liquid interfaces, thin films, and solution and solid samples. The post‐sample section consists of a 1 m WAXS section with two linear gas detectors, a vacuum bellows (1–4 m), a two‐beamstop system and the SAXS detector system, all situated on a motorized optical bench for motion in six degrees of freedom. In particular, the vacuum bellows of a large inner diameter (260 mm) provides continuous changes of the sample‐to‐detector distance under vacuum. Synchronized SAXS and WAXS measurements are realized via a data‐acquisition protocol that can integrate the two linear gas detectors for WAXS and the area detector for SAXS (gas type or Mar165 CCD); the protocol also incorporates sample changing and temperature control for programmable data collection. The performance of the instrument is illustrated via several different measurements, including (1) simultaneous SAXS/WAXS and differential scanning calorimetry for polymer crystallization, (2) structural evolution with a large ordering spacing of ∼250 nm in a supramolecular complex, (3) SAXS for polymer blends under in situ drawing, (4) SAXS and anomalous SAXS for unilamellar lipid vesicles and metalloprotein solutions, (5) anomalous GISAXS for oriented membranes of Br‐labeled lipids embedded with peptides, and (6) GISAXS for silicate films formed in situ at the air–water interface.

The Laser Interferometer Space Antenna (LISA) has two scientific objectives of cosmological focus: to probe the expansion rate of the universe, and to understand stochastic gravitational-wave backgrounds and their implications for early universe and particle physics, from the MeV to the Planck scale. However, the range of potential cosmological applications of gravitational-wave observations extends well beyond these two objectives. This publication presents a summary of the state of the art in LISA cosmology, theory and methods, and identifies new opportunities to use gravitational-wave observations by LISA to probe the universe.

With the popularity of digital camera, digital image processing is getting more important. One of the most common problems in digital photographing is motion blur. The research in solving the problem of motion blur efficiently is called motion deblur. When taking a photograph, the shaking of camera is the reason causing blurred image. The blur process can be formulated as the image takes convolution operation with the shaking path, which is also known as point spread function. One of the well-known deconvolution algorithms in solving the convolution problem is Richardson-Lucy algorithm. Although Richardson-Lucy can recover the image from blurred image, there are unexpected ringing artifacts in the deblurred image. To solve ringing is the main purpose in recent researches. In our research, by pre-detecting the region and intensity of ringing in the image, we propose an improved Richardson-Lucy algorithm to deblur image and suppress the ringing.

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Production technology has increased rapidly with the development of industrial technology. Conventional human visual inspection is insufficient for conducting quality control under this increased capacity. Therefore, high-speed and high-accuracy automated optical inspection is becoming increasingly crucial. In this article, we propose an automated inspection method for a compact camera lens using a circle Hough transformation, weighted Sobel filter, and polar transformation. Our analysis of defects in the compact camera lens identified problems including of the circular texture and the non-fixed position of the inspection region. To overcome these problems, we design an inspection algorithm for locating and inspecting a circular region. A machine learning support vector machine method is then applied for obtaining a precise detection result. The experimental results show that the proposed inspection method is suitable for detecting defects in a complicated circular inspection region, and that the proposed system exhibited high performance.

One of the most common artifacts in digital photography is motion blur. When capturing an image under dim light by using a handheld camera, the tendency of the photographer’s hand to shake causes the image to blur. In response to this problem, image deblurring has become an active topic in computational photography and image processing in recent years. From the view of signal processing, image deblurring can be reduced to a deconvolution problem if the kernel function of the motion blur is assumed to be shift invariant. However, the kernel function is not always shift invariant in real cases; for example, in-plane rotation of a camera or a moving object can blur different parts of an image according to different kernel functions. An image that is degraded by multiple blur kernels is called a nonuniform blur image. In this paper, we propose a novel single image deblurring algorithm for nonuniform motion blur images that is blurred by moving object. First, a proposed uniform defocus map method is presented for measurement of the amounts and directions of motion blur. These blurred regions are then used to estimate point spread functions simultaneously. Finally, a fast deconvolution algorithm is used to restore the nonuniform blur image. We expect that the proposed method can achieve satisfactory deblurring of a single nonuniform blur image.

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