This review highlights the recent progress in synthesizing some representative metal-oxide nanocrystals (MONCs) with controlled magnetic, electronic, and optical properties for potentially important ...technological applications. It first introduces the synthesis of MONCs of magnetite (Fe3O4), ferrite (MFe2O4), and hollow Fe3O4 with controlled magnetic properties. It then highlights the potentials of these nanocrystals (NCs) as highly effective contrast enhancement agents for magnetic resonance imaging (MRI) and as efficient nanoplatforms for target specific drug delivery. The review further surveys some typical high-temperature solution-phase approaches to the common semiconductive MONCs of indium tin oxide (ITO, In2O3·xSnO2)/tin oxide (SnO2), zinc oxide (ZnO), titanium oxide (TiO2), and copper oxide (Cu2O or CuO) with controlled band-gap energies and optical properties for optoelectronics, photocatalysis, and sensor applications.
We propose a novel discrete Fourier transform (DFT)-based direction of arrival (DOA) estimation by a virtual array extension using simple multiplications for frequency modulated continuous wave ...(FMCW) radar. DFT-based DOA estimation is usually employed in radar systems because it provides the advantage of low complexity for real-time signal processing. In order to enhance the resolution of DOA estimation or to decrease the missing detection probability, it is essential to have a considerable number of channel signals. However, due to constraints of space and cost, it is not easy to increase the number of channel signals. In order to address this issue, we increase the number of effective channel signals by generating virtual channel signals using simple multiplications of the given channel signals. The increase in channel signals allows the proposed scheme to detect DOA more accurately than the conventional scheme while using the same number of channel signals. Simulation results show that the proposed scheme achieves improved DOA estimation compared to the conventional DFT-based method. Furthermore, the effectiveness of the proposed scheme in a practical environment is verified through the experiment.
This letter proposes a joint discrete Fourier transform (DFT)-estimation of signal parameters via rotational invariance techniques (ESPRIT) estimator for time-of-arrival (TOA) and ...direction-of-arrival (DOA) in vehicle frequency-modulated continuous-wave (FMCW) radars. Since the vehicle FMCW radar should recognize vehicles in the side/rear area when the driver initiates a lane change, the estimation of the joint TOA/DOA between the radar and targets is an important issue for solving complicated location tasks. However, conventional joint estimation methods such as 2D-ESPRIT and 2D-multiple signal classification (MUSIC) cannot be adopted for real-time implementation due to their high computational loads. To satisfy the required accuracy specifications and reduce complexity compared with the conventional estimator, we propose a low-complexity joint TOA and DOA estimator that uses the combined DFT-ESPRIT algorithm for FMCW radars. The performance of the proposed estimation in multitarget environments was derived and compared with the Monte Carlo simulation results. The root-mean-square error (RMSE) of the proposed method was compared with that of 2D-ESPRIT with various parameters. To verify the performance of the proposed combination method, we implemented the FMCW radar and verified its performance in an anechoic chamber environment.
Video scene graph generation (ViDSGG), the creation of video scene graphs that helps in deeper and better visual scene understanding, is a challenging task. Segment-based and sliding-window based ...methods have been proposed to perform this task. However, they all have certain limitations. This study proposes a novel deep neural network model called VSGG-Net for video scene graph generation. The model uses a sliding window scheme to detect object tracklets of various lengths throughout the entire video. In particular, the proposed model presents a new tracklet pair proposal method that evaluates the relatedness of object tracklet pairs using a pretrained neural network and statistical information. To effectively utilize the spatio-temporal context, low-level visual context reasoning is performed using a spatio-temporal context graph and a graph neural network as well as high-level semantic context reasoning. To improve the detection performance for sparse relationships, the proposed model applies a class weighting technique that adjusts the weight of sparse relationships to a higher level. This study demonstrates the positive effect and high performance of the proposed model through experiments using the benchmark dataset VidOR and VidVRD.
We propose a frequency-modulated continuous wave (FMCW) radar estimation algorithm with high resolution and low complexity. The fast Fourier transform (FFT)-based algorithms and multiple signal ...classification (MUSIC) algorithms are used as algorithms for estimating target parameters in the FMCW radar systems. FFT-based and MUSIC algorithms have tradeoff characteristics between resolution performance and complexity. While FFT-based algorithms have the advantage of very low complexity, they have the disadvantage of a low-resolution performance; that is, estimating multiple targets with similar parameters as a single target. On the other hand, subspace-based algorithms have the advantage of a high-resolution performance, but have a problem of very high complexity. In this paper, we propose an algorithm with reduced complexity, while achieving the high-resolution performance of the subspace-based algorithm by utilizing the advantages of the two algorithms; namely, the low-complexity advantage of FFT-based algorithms and the high-resolution performance of the MUSIC algorithms. The proposed algorithm first reduces the amount of data used as input to the subspace-based algorithm by using the estimation results obtained by FFT. Secondly, it significantly reduces the range of search regions considered for pseudo-spectrum calculations in the subspace-based algorithm. The simulation and experiment results show that the proposed algorithm achieves a similar performance compared with the conventional and low complexity MUSIC algorithms, despite its considerably lower complexity.
Recently, Doppler radar-based foot gesture recognition has attracted attention as a hands-free tool. Doppler radar-based recognition for various foot gestures is still very challenging. So far, no ...studies have yet dealt deeply with recognition of various foot gestures based on Doppler radar and a deep learning model. In this paper, we propose a method of foot gesture recognition using a new high-compression radar signature image and deep learning. By means of a deep learning AlexNet model, a new high-compression radar signature is created by extracting dominant features via Singular Value Decomposition (SVD) processing; four different foot gestures including kicking, swinging, sliding, and tapping are recognized. Instead of using an original radar signature, the proposed method improves the memory efficiency required for deep learning training by using a high-compression radar signature. Original and reconstructed radar images with high compression values of 90%, 95%, and 99% were applied for the deep learning AlexNet model. As experimental results, movements of all four different foot gestures and of a rolling baseball were recognized with an accuracy of approximately 98.64%. In the future, due to the radar’s inherent robustness to the surrounding environment, this foot gesture recognition sensor using Doppler radar and deep learning will be widely useful in future automotive and smart home industry fields.
This paper proposes a high-efficiency super-resolution frequency-modulated continuous-wave (FMCW) radar algorithm based on estimation by fast Fourier transform (FFT). In FMCW radar systems, the ...maximum number of samples is generally determined by the maximum detectable distance. However, targets are often closer than the maximum detectable distance. In this case, even if the number of samples is reduced, the ranges of targets can be estimated without degrading the performance. Based on this property, the proposed algorithm adaptively selects the number of samples used as input to the super-resolution algorithm depends on the coarsely estimated ranges of targets using the FFT. The proposed algorithm employs the reduced samples by the estimated distance by FFT as input to the super resolution algorithm instead of the maximum number of samples set by the maximum detectable distance. By doing so, the proposed algorithm achieves the similar performance of the conventional multiple signal classification algorithm (MUSIC), which is a representative of the super resolution algorithms while the performance does not degrade. Simulation results demonstrate the feasibility and performance improvement provided by the proposed algorithm; that is, the proposed algorithm achieves average complexity reduction of 88% compared to the conventional MUSIC algorithm while achieving its similar performance. Moreover, the improvement provided by the proposed algorithm was verified in practical conditions, as evidenced by our experimental results.
This paper proposes a low complexity multiple-signal-classifier (MUSIC)-based direction-of-arrival (DOA) detection algorithm for frequency-modulated continuous-wave (FMCW) vital radars. In order to ...reduce redundant complexity, the proposed algorithm employs characteristics of distance between adjacent arrays having trade-offs between field of view (FOV) and resolution performance. First, the proposed algorithm performs coarse DOA estimation using fast Fourier transform. On the basis of the coarse DOA estimation, the number of channels as input of the MUSIC algorithm are selected. If the estimated DOA is smaller than 30°, it implies that there is an FOV margin. Therefore, the proposed algorithm employs only half of the channels, that is, it is the same as doubling the spacing between arrays. By doing so, the proposed algorithm achieves more than 40% complexity reduction compared to the conventional MUSIC algorithm while achieving similar performance. By experiments, it is shown that the proposed algorithm despite the low complexity is enable to distinguish the adjacent DOA in a practical environment.
Monodisperse 11 nm indium tin oxide (ITO) nanocrystals (NCs) were synthesized by thermal decomposition of indium acetylacetonate, In(acac)3, and tin bis(acetylacetonate)dichloride, Sn(acac)2Cl2, at ...270 °C in 1-octadecene with oleylamine and oleic acid as surfactants. Dispersed in hexane, these ITO NCs were spin-cast on centimeter-wide glass substrates, forming uniform ITO NC assemblies with root-mean-square roughness of 2.9 nm. The assembly thickness was controlled by ITO NC concentrations in hexane and rotation speeds of the spin coater. Via controlled thermal annealing at 300 °C for 6 h under Ar and 5% H2, the ITO NC assemblies became conductive and transparent with the 146 nm-thick assembly showing 5.2 × 10–3 Ω·cm (R s = 356 Ω/sq) resistivity and 93% transparency in the visible spectral rangethe best values ever reported for ITO NC assemblies prepared from solution phase processes. The stable hexane dispersion of ITO NCs was also readily spin-cast on polyimide (T g ∼360 °C), and the resultant ITO assembly exhibited a comparable conductivity and transparency to the assembly on a glass substrate. The reported synthesis and assembly provide a promising solution to the fabrication of transparent and conducting ITO NCs on flexible substrates for optoelectronic applications.
In order to achieve a good and competitive FPSO design, the building cost and the motion performances are the two most critical and conflicting KPIs to be considered. In this study, the author's ...previous work (Lee, et al., 2021) on the optimization of an FPSO's hull dimensions with 1800 MBBLs storage capacity at Brazil field was extended using a multi-objective parametric optimization with the hull steel weight and the operability which are closely related to the building cost and the operational cost during the lifetime, respectively. For the purpose of more realistic and practical FPSO design, the constraints related to crew comfort and the safe helicopter take-off and landing operation were newly added. Also, the green water on deck was calculated accurately to check the suitability of the designed freeboard height using a newly developed real-time calculation module for the relative wave elevations. With aids of this updated optimization formulation, we presented multiple optimal FPSO dimensions expressed as a Pareto set which aids FPSO designers to conveniently select the practical and competitive dimensions. The excellence of the developed approach was verified by comparing the optimization results with those of FPSOs dimensioned for operation at West Africa and Brazil field.
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