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Registration of unmanned aerial vehicle laser scanning (ULS) and ground light detection and ranging (LiDAR) point clouds in forests is critical to create a detailed representation of a forest structure and an accurate inversion of forest parameters. However, forest occlusion poses challenges for marker-based registration methods, and some marker-free automated registration methods have low efficiency due to the process of object (e.g., tree, crown) segmentation. Therefore, we use a divide-and-conquer strategy and propose an automated and efficient method to register ULS and ground LiDAR point clouds in forests. Registration involves coarse alignment and fine registration, where the coarse alignment of point clouds is divided into vertical and horizontal alignment. The vertical alignment is achieved by ground alignment, which is achieved by the transformation relationship between normal vectors of the ground point cloud and the horizontal plane, and the horizontal alignment is achieved by canopy projection image matching. During image matching, vegetation points are first distinguished by the ground filtering algorithm, and then, vegetation points are projected onto the horizontal plane to obtain two binary images. To match the two images, a matching strategy is used based on canopy shape context features, which are described by a two-point congruent set and canopy overlap. Finally, we implement coarse alignment of ULS and ground LiDAR datasets by combining the results of ground alignment and image matching and finish fine registration. Also, the effectiveness, accuracy, and efficiency of the proposed method are demonstrated by field measurements of forest plots. Experimental results show that the ULS and ground LiDAR data in different plots are registered, of which the horizontal alignment errors are less than 0.02 m, and the average runtime of the proposed method is less than 1 second.

Heterogeneous face recognition between color image and depth image is a much desired capacity for real world applications where shape information is looked upon as merely involved in gallery. In this paper, we propose a cross-modal deep learning method as an effective and efficient workaround for this challenge. Specifically, we begin with learning two convolutional neural networks (CNNs) to extract 2D and 2.5D face features individually. Once trained, they can serve as pre-trained models for another two-way CNN which explores the correlated part between color and depth for heterogeneous matching. Compared with most conventional cross-modal approaches, our method additionally conducts accurate depth image reconstruction from single color image with Conditional Generative Adversarial Nets (cGAN), and further enhances the recognition performance by fusing multi-modal matching results. Through both qualitative and quantitative experiments on benchmark FRGC 2D/3D face database, we demonstrate that the proposed pipeline outperforms state-of-the-art performance on heterogeneous face recognition and ensures a drastically efficient on-line stage.

Terrestrial LiDAR systems have received lots of attention on three-dimensional (3D) structure reconstruction for trees, especially on the branches skeleton generation. On this basis, a method is proposed to add leaves structures based on point density by dividing small cube in the canopy to reduce the influence of uneven distribution of point cloud, combining gap fraction model to retrieve leaf area of a tree using terrestrial LiDAR data. It is successfully applied to reconstruct 3D trees using points data simulated by ray tracing algorithm as well as field measured points data. The relative error of leaf area between reconstructed and real structure is less than 0.9%. Meanwhile, the most relative error of directional gap fraction is also less than 4.1%. The experimental results prove that the method has gotten a satisfied consistency on visual sense and quantitative evaluation between the 3D structure reconstructed and real structure.

Determination of isocarbophos by cathodically sweeping oscilliopolarography is described. In a 1.0×10−5 mol/L sodium dodecylbenzene sulfonate (SDS)+0.1 mol/L HAC-NaAC (pH=4.0) buffer medium, isocarbophos and its alkaline hydrolysate exhibited sensitive second derivative wave at −0.50 V and −0.48 V respectively. The peak current was linearly proportional to the concentration of isocarbophos in the range of 5.40×10−6−1.05×10−4 mol/L by detecting isocarbophos directly. The detection limit was 3.60×10−6 mol/L with the relative standard derivation (RSD) of 7.3%. By employing an alkaline hydrolysis, the peak current was linearly proportional to the concentration of isocarbophos in the range from 7.70×10−7 mol/L to 1.24×10−4 mol/L, and the detection limit was 5.80×10−7 mol/L with RSD of 3.1%. The hydrolysis procedure and the electrode reaction were studied by voltammetry.

Nitric oxide can be oxidized to NO − 2 (then to NO − 3 ) and reduced to N 2 O at a glassy carbon electrode modified with the film of poly(neutral red). When the modified electrode is further coated with a thin Nafion film, the interference of NO − 2 can be almost thoroughly eliminated, and the electrode can be employed to detect nitric oxide.

Determination of omethoate by cathodically sweeping oscillopolarography is described. The product of the alkaline hydrolysis exhibited a sensitive second derivative wave at −0.50 V (vs. SCE) in a 1.0 ×10−5mol/L sodium dodecylbenzene sulfonate (SDBS)+0.1 mol/L HAc-NaAc (pH 4.0) buffer. The peak current was linearly proportional to the concentration of omethoate in the range from 6.4×10−7 to 5.1×10−5 mol/L. The detection limit is 2.0×10−7 mol/L with the relative standard derivation (RSD) of 3.5%. The hydrolysis procedure and the electrode reaction were studied by voltammetry.

Electrochemical redox of hemoglobin at poly(o-phenylenediamine) coated glass carbon electrodes or at bare glass carbon electrodes promoted byo-phenylenediamine have been investigated. The electrochemical characters of poly(o-phenylenediamine) films have also been studied by using cyclic voltammetry and potential-step chronoamperometry as well as current-step chronocoulometry techniques. A possible catalyzing mechanism for hemoglobin is proposed.

The voltammetric behavior of concanavalin A at the bare silver electrode is described. Cyclic voltammograms show a pair of well-defined redox peaks for concanavalin A in the medium of phosphate buffer(pH=7.0) with electrochemical reaction rate constant ofK 2=0.053 s−1 and electron transfer number ofn=2. Moreover, both the oxidation currents and the reduction currents have linear relationship with concanavalin A concentrations in the range of 1.0×10−6∼2.0×10−5 mol/L, which can be used as an analytical method for determining concanavalin A concentration.

A novel electrophoresis technique, in which a strip of perflurosulfonic-acid (nafion 117) membrane was used to replace the conventional separation column and liquid buffer solution within, was developed and employed to separate the mixture of dopamine and epinephrine under a low separation voltage of 100 V with quadruple pulses amperometry detection. It was showed that the so-called Nafion membrane electrophoresis could be one of very simple and easy method and has the potentiality to be used to separate and analyze some small organic biologic molecules.

A re-utilizable piezoelectric crystal (PC) immunosensor for thyroidal triiodothyronine (T3) has been developed. The crystal was coated with protein A and then reacted with T3 antibody. T3 could be detected in the range of 0.5×10−6 g/L to 10.0×10−6g/L by the, system. Crystal was regenerated by saturating with T3 and subsequent binding of a new anti-T3 antibody layer. The T3 assay could be repeated up to 5 times using each crystal.

A surface acoustic wave (SAW) piezoelectric device with a dual-path SAW delay line oscillator configuration has been developed to detect nitrogen dioxide (NO 2 ) gas. One delay line is coated with a Langmuir-Blodgett (LB) film of copper tetrasulphonated phthalocyanine (CuTsPc), while the other is uncoated. NO 2 gas can be selectively abosorbed by the CuTsPc LB film and then alters the SAW characteristics, which in turn causes the oscillation frequency to change. The concentration of NO 2 can be detected by measuring the relative change in the frequency of the two oscillators. The CuTsPc LB film-coated SAW device has been demonstrated to be sensitive to low concentrations of NO 2 gas. There is a linear relationship between NO 2 concentration and frequency change under 12 ppm NO 2 concentration. The sensitivity of the device is about 128 Hz/ppm NO 2 . The response time is 10 min, and the recovery is 40 min. It can be applied as a small, inexpensive and sensitive NO 2 gas sensor.

The finite element method (FEM) employed to model the temperature field in a heated silicon plane was discussed, since optimum designing of the micro-silicon structure would be the basis of a micro-machined silicon-based thermal biosensor. In this research, the heat flow originally generated by the enzymatic reaction was conducted in the anisotropically etched silicon and collected by a thermopile array. Fourier's law and Laplace's equation were utilized to build the temperature field equations under appropriate boundary conditions in two-dimensions Cartesian coordinates, while FEM was used to calculate the temperature field and model conduction. Meanwhile, several available results for optimum design are reported.

Determination of omethoate by modified PQC (piezoelectric quartz crystal) sensor is described. Several modified films were studied and compared. Omethoate of 0.1-10 ppm can be determined directly and sensitively with PVC-dioctyl sebacate film modified PQC. The modified crystal has good reversibility and reproductivity. The lifetime is about 1 month.