Hybrid nanomaterials have received voluminous interest due to the combination of unique properties of organic and inorganic component in one material. In this class, magnetic polymer nanocomposites are of particular interest because of the combination of excellent magnetic properties, stability, and good biocompatibility. Organic–inorganic magnetic nanocomposites can be prepared by in situ, ex situ, microwave reflux, co-precipitation, melt blending, and ceramic–glass processing and plasma polymerization techniques. These nanocomposites have been exploited for in vivo imaging, as superparamagnetic or negative contrast agents, drug carriers, heavy metal adsorbents, and magnetically recoverable photocatalysts for degradation of organic pollutants. This review article is mainly focused on fabrication of magnetic polymer nanocomposites and their applications. Different types of magnetic nanoparticles, methods of their synthesis, properties, and applications have also been reviewed briefly. The review also provides detailed insight into various types of magnetic nanocomposites and their synthesis. Diverse applications of magnetic nanocomposites including environmental and biomedical uses have been discussed.

Magnetic polymer nanocomposites for environmental and biomedical applications

A digital micromirror device (DMD) is a product of micromechanics. The DMD employs numerous micromirrors as the actuating components to switch small portions of light on and off. During the past few decades, such devices have been widely applied in digital light processing technology. The expanding range of applications makes the DMD increasingly important in various research aspects. Recent advances demonstrate that the DMD is potentially better than the traditional liquid crystal spatial light modulator in speed, spectrum sensitivity, and polarization modulation. These characteristics have been verified in a series of recently reported experiments. This review summarizes the related theory, experimental techniques, and applications for wavefront shaping with DMDs in both statically shaping various spatial modes and dynamically compensating for wavefront distortion caused by the scattering medium.

https://onlinelibrary.wiley.com/doi/pdf/10.1002/andp.201500111

Tailoring light with a digital micromirror device

The diverse vision systems found in nature can provide interesting design inspiration for imaging devices, ranging from optical subcomponents to digital cameras and visual prostheses, with more desirable optical characteristics compared to conventional imagers. The advantages of natural vision systems include high visual acuity, wide field of view, wavelength-free imaging, improved aberration correction and depth of field, and high motion sensitivity. Recent advances in soft materials, ultrathin electronics, and deformable optoelectronics have facilitated the realization of novel processes and device designs that mimic biological vision systems. This review highlights recent progress and continued efforts in the research and development of bioinspired artificial eyes. At first, the configuration of two representative eyes found in nature: a single-chambered eye and a compound eye, is explained. Then, advances in bioinspired optic components and image sensors are discussed in terms of materials, optical/mechanical designs, and integration schemes. Subsequently, novel visual prostheses as representative application examples of bioinspired artificial eyes are described.

Bioinspired Artificial Eyes: Optic Components, Digital Cameras, and Visual Prostheses

The natural compound eye has received much attention in recent years due to its remarkable properties, such as its large field of view (FOV), compact structure, and high sensitivity to moving objects. Many studies have been devoted to mimicking the imaging system of the natural compound eye. The paper gives a review of state-of-the-art artificial compound eye imaging systems. Firstly, we introduce the imaging principle of three types of natural compound eye. Then, we divide current artificial compound eye imaging systems into four categories according to the difference of structural composition. Readers can easily grasp methods to build an artificial compound eye imaging system from the perspective of structural composition. Moreover, we compare the imaging performance of state-of-the-art artificial compound eye imaging systems, which provides a reference for readers to design system parameters of an artificial compound eye imaging system. Next, we present the applications of the artificial compound eye imaging system including imaging with a large FOV, imaging with high resolution, object distance detection, medical imaging, egomotion estimation, and navigation. Finally, an outlook of the artificial compound eye imaging system is highlighted.

https://iopscience.iop.org/article/10.1088/1748-3190/aaffb5/pdf

Review of state-of-the-art artificial compound eye imaging systems.

An artificial compound eye system is the bionic system of natural compound eyes with much wider field-of-view, better capacity to detect moving objects and higher sensitivity to light intensity than ordinary single-aperture eyes. In recent years, renewed attention has been paid to the artificial compound eyes, due to their better characteristics inheriting from insect compound eyes than ordinary optical imaging systems. This paper provides a comprehensive survey of the state-of-the-art work on artificial compound eyes. This review starts from natural compound eyes to artificial compound eyes including their system design, theoretical development and applications. The survey of artificial compound eyes is developed in terms of two main types: planar and curved artificial compound eyes. Finally, the most promising future research developments are highlighted.

Artificial compound eye: a survey of the state-of-the-art

We propose a low complexity complex valued Sphere Decoding (CV-SD) algorithm, referred to as Circular Sphere Decoding (CSD) which is applicable to multiple-input multiple-output (MIMO) systems with arbitrary two dimensional (2D) constellations. CSD provides a new constraint test. This constraint test is carefully designed so that the element-wise dependency is removed in the metric computation for the test. As a result, the constraint test becomes simple to perform without restriction on its constellation structure. By additionally employing this simple test as a prescreening test, CSD reduces the complexity of the CV-SD search. We show that the complexity reduction is significant while its maximum-likelihood (ML) performance is not compromised. We also provide a powerful tool to estimate the pruning capacity of any particular search tree. Using this tool, we propose the Predict-And-Change strategy which leads to a further complexity reduction in CSD. Extension of the proposed methods to soft output SD is also presented.

Circular Sphere Decoding: A Low Complexity Detection for MIMO Systems with General Two-dimensional Signal Constellations

We propose a low-complexity, complex-valued sphere decoding (CV-SD) algorithm, which is referred to as circular sphere decoding (CSD) and is applicable to multiple-input–multiple-output (MIMO) systems with arbitrary 2-D constellations. CSD provides a new constraint test. This constraint test is carefully designed so that the elementwise dependence is removed in the metric computation for the test. As a result, the constraint test becomes simple to perform without restriction on its constellation structure. By additionally employing this simple test as a prescreening test, CSD reduces the complexity of the CV-SD search. We show that the complexity reduction is significant, while its maximum-likelihood (ML) performance is not compromised. We also provide a powerful tool to estimate the pruning capacity of any particular search tree. Using this tool, we propose the predict-and-change strategy, which leads to a further complexity reduction in CSD. Extension of the proposed methods to soft output sphere decoding (SD) is also presented.

Circular Sphere Decoding: A Low Complexity Detection for MIMO Systems With General Two-dimensional Signal Constellations

In this paper, we propose a maximum likelihood (ML)-like performance reduced computational complexity sorted orthotope sphere decoding (OSD), and zero forced (ZF) sorted OSD algorithms for the spatial multiplexing (SM) in a multiple-input multiple-output (MIMO) system. In comparison with the original OSD our technique reduces the number of partial Euclidean distance (PED) computations by up to 28%, and 25% for QPSK and 16-QAM 4×4 MIMO systems, respectively.

/pdf/reduced-complexity-orthotope-sphere-decoding-for-multiple-2pegymara3.pdf

Reduced-complexity orthotope sphere decoding for multiple-input multiple-output antenna system

In this work, a method for predicting the pruning potential of a sphere constraint (SC) for sphere decoding (SD) is developed Because the direct prediction of the pruning potential is not easy, the orthotope constraint (OC), an approximation of SC, is used instead of SC This pruning potential prediction makes it possible to increase pruning at the root of the search tree in SD, considering it is the most desirable location for pruning

Predicting the pruning potential in sphere decoding for multiple-input multiple-output detection

It is expected that the techniques of optical imaging through turbid media enables non-invasive imaging through human skin and biological tissues. In recent years, many researches have shown that imaging through turbid media can be made possible by measuring the transmission matrix (TM) of the turbid medium and utilizing it for image recovery. However, this TM based image recovery requires a huge amount of data acquisition and post signal processing of them. Very recently, there were new results that this problem of huge data acquisition and processing can be resolved by using the compressed sensing (CS) framework. CS is a relatively new signal acquisition and reconstruction framework which makes possible to recover the signal of interest correctly with significantly smaller number of signal measurements. In this paper, the TM-based image recovery in imaging through turbid media is reviewed and the recent progress made by using CS is introduced.

Hwanchol Jang

Papers

Circular Sphere Decoding: A Low Complexity Detection for MIMO Systems with General Two-dimensional Signal Constellations

Circular Sphere Decoding: A Low Complexity Detection for MIMO Systems With General Two-dimensional Signal Constellations

Reduced-complexity orthotope sphere decoding for multiple-input multiple-output antenna system

Predicting the pruning potential in sphere decoding for multiple-input multiple-output detection

Recent Progress in Computational Imaging Through Turbid Media