In this work, using 0.2 µm GaAs modulation doped FET (MODFET), a high performance downconverter MMIC was developed for direct broadcasting satellite (DBS) applications. The downconverter MMIC showed a noise figure of 4.3 dB which is lower by 5 dB than conventional ones, and required only a low LO power of -10 dBm for normal DBS operation. At a low LO power of -10 dBm, the power consumption was 175 mW, which is lower than 50 percent of conventional ones. The frequency response of conversion gain exhibited a low gain ripple of 0.9 dB, and the LO leakage power was suppressed to a lower value than -30 dBm under a LO input power of -10 dBm. The fabricated chip exhibited a small size of 0.840.9 mm2. The objectives of this work are to improve the traditional direct broadcasting satellite (DBS) downconverters by an efficient circuit design and to describe the techniques employed in the design.

The classification of human motion is an important aspect of monitoring pedestrian traffic. This requires the development of advanced surveillance and monitoring systems. Methods to achieve this have been proposed using micro-Doppler radars. However, reliable long-term data and/or complicated procedures are needed to classify motion accurately with these conventional methods because their accuracy and real-time capabilities are invariably inadequate. This paper proposes an accurate and real-time method for classifying the movements of pedestrians using ultra wide-band (UWB) Doppler radar to overcome these problems. The classification of various movements is achieved by extracting feature parameters based on UWB Doppler radar images and their radial velocity distributions. Experiments were carried out assuming six types of pedestrian movements (pedestrians swinging both arms, swinging only one arm, swinging no arms, on crutches, pushing wheelchairs, and seated in wheelchairs). We found they could be classified using the proposed feature parameters and a k-nearest neighbor algorithm. A classification accuracy of 96% was achieved with a mean calculation time of 0.55s. Moreover, the classification accuracy was 99% using our proposed method for classifying three groups of pedestrian movements (normal walkers, those on crutches, and those in wheelchairs).

An optical intensity distribution under light irradiation in the organic photovoltaic cell affects the absorbance of the active layer, which determines the photovoltaic performance. In this research, we evaluated the optimum thickness of the organic active layer with poly[4,8-bis(5-(2-ethylhexyl)thiophen-2-yl)benzo[1,2-b;4,5-b']dithiophene-2,6-diyl-alt-(4-(2-ethylhexyl)-3-fluorothieno[3,4-b]thiophene-)-2-carboxylate-2-6-diyl)] and [6,6]-phenyl C71-butyric acid methyl ester. The spectral response of external quantum efficiency was good agreement with the simulated optical intensity distribution within a device stack as a function of the position and the wavelength. As a result, the highest photoconversion efficiency of 10.1% was achieved for the inverted device structure.

Nowadays, semiconductor quantum dots have attracted intense attention as emissive materials for light-emitting diodes, due to their high photoluminescence quantum yield and the controllability of their photoluminescence spectrum by changing the core diameter. In general, semiconductor quantum dots contain large amounts of organic ligands around the core/shell structure to obtain dispersibility in solution, which leads to solution processability of the semiconductor quantum dot. Furthermore, organic ligands, such as straight alkyl chains, are generally insulating materials, which affects the carrier transport in thin-film light-emitting diodes. However, a detailed investigation has not been performed yet. In this paper, we investigated the luminance characteristics of quantum-dot light-emitting diodes containing ZnCuInS2 quantum dots with different carbon chain lengths of alkyl thiol ligands as emitting layers. By evaluating the CH2/CH3 ratio from Fourier-transform infrared spectra and thermal analysis, it was found that approximately half of the oleylamine ligands were converted to alkyl thiol ligands, and the evaporation temperature increased with increasing carbon chain length of the alkyl thiol ligands based on thermogravimetric analysis. However, the photoluminescence quantum yield and the spectral shape were almost the same, even after the ligand-exchange process from the oleylamine ligand to the alkyl thiol ligand. The peak wavelength of the photoluminescence spectra and the photoluminescence quantum yield were approximately 610 nm and 10%, respectively, for all samples. In addition, the surface morphology of spin coated ZnCuInS2 quantum-dot layers did not change after the ligand-exchange process, and the root-mean-square roughness was around 1 nm. Finally, the luminance efficiency of an inverted device structure increased with decreasing carbon chain length of the alkyl thiol ligands, which were connected around the ZnCuInS2 quantum dots. The maximum luminance and current efficiency were 86 cd/m2 and 0.083 cd/A, respectively.

Recent studies have focused on developing security systems using micro-Doppler radars to detect human bodies. However, the resolution of these conventional methods is unsuitable for identifying bodies and moreover, most of these conventional methods were designed for a solitary or sufficiently well-spaced targets. This paper proposes a solution to these problems with an image separation method for two closely spaced pedestrian targets. The proposed method first develops an image of the targets using ultra-wide-band (UWB) Doppler imaging radar. Next, the targets in the image are separated using a supervised learning-based separation method trained on a data set extracted using a range profile. We experimentally evaluated the performance of the image separation using some representative supervised separation methods and selected the most appropriate method. Finally, we reject false points caused by target interference based on the separation result. The experiment, assuming two pedestrians with a body separation of 0.44m, shows that our method accurately separates their images using a UWB Doppler radar with a nominal down-range resolution of 0.3m. We describe applications using various target positions, establish the performance, and derive optimal settings for our method.

A solution-processed red-sensitive organic photoconductive device was demonstrated by using soluble nickel-phthalocyanine. We found that a ratio of four nickel-phthalocyanine regioisomers was important factor for the high optical-electrical conversion efficiency. A maximum external quantum efficiency of device of 0.83% was achieved by optimizing the device structure.

We demonstrated the reduced surface roughness of poly (3-hexylthiophene) (P3HT):(6,6)-phenyl-C61-butyric acid methyl ester (PCBM) thin films with different ratios fabricated by the electrospray deposition (ESD) method. Aggregated structures were observed at the lower voltage, and the uniformity became bad at the higher voltage. Anyway, the minimum root mean square (RMS) roughness was 1.46 nm by optimizing the applied voltage.

We report a real time method to monitor the chemical reaction in microdroplets, which contain an organic dye, 5(6)-carboxynaphthofluorescein and a CdSe/ZnS quantum dot using fluorescence spectra. Especially, the relationship between the droplet size and the reaction rate of the two reagents was investigated by changing an injection speed.

In this paper, we investigate inverse problems of the interval query problem in application to data mining. Let I be the set of all intervals on U = {1, 2, , n}. Consider an objective function f(I), conditional functions ui(I) on I, and define an optimization problem of finding the interval I maximizing f(I) subject to ui(I) > Ki for given real numbers Ki (i = 1, 2, , h). We propose efficient alogorithms to solve the above optimization problem if the objective function is either additive or quotient, and the conditional functions are additive, where a function f is additive if f(I) = ΣiIf^(i) extending a function f^ on U, and quotient if it is represented as a quotient of two additive functions. We use computational-geometric methods such as convex hull, range searching, and multidimensional divide-and-conquer.

The imaging of humans using radar is promising for surveillance systems. Although conventional radar systems detect the presence or position of intruders, it is difficult to acquire shape and motion details because the resolution is insufficient. This paper presents a high-resolution human imaging algorithm for an ultra-wideband (UWB) Doppler radar. The proposed algorithm estimates three-dimensional human images using interferometry and, using velocity information, rejects false images created by the interference of body parts. Experiments verify that our proposed algorithm achieves adequate pedestrian imaging. In addition, accurate shape and motion parameters are extracted from the estimated images.