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  • MDPI AG  (17)
  • 1
    Online Resource
    Online Resource
    Ultrasonic Al2O3 Ceramic Thermometry in High-Temperature Oxidation Environment
    MDPI AG ; 2016
    In:  Sensors Vol. 16, No. 11 ( 2016-11-11), p. 1905-
    Details
    In: Sensors, MDPI AG, Vol. 16, No. 11 ( 2016-11-11), p. 1905-
    Type of Medium: Online Resource
    ISSN: 1424-8220
    URL: Article
    DOI: 10.3390/s16111905
    Language: English
    Publisher: MDPI AG
    Publication Date: 2016
    detail.hit.zdb_id: 2052857-7
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  • 2
    Online Resource
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    An Improved YOLO Model for UAV Fuzzy Small Target Image Detection
    MDPI AG ; 2023
    In:  Applied Sciences Vol. 13, No. 9 ( 2023-04-26), p. 5409-
    Details
    In: Applied Sciences, MDPI AG, Vol. 13, No. 9 ( 2023-04-26), p. 5409-
    Abstract: High-altitude UAV photography presents several challenges, including blurry images, low image resolution, and small targets, which can cause low detection performance of existing object detection algorithms. Therefore, this study proposes an improved small-object detection algorithm based on the YOLOv5s computer vision model. First, the original convolution in the network framework was replaced with the SPD-Convolution module to eliminate the impact of pooling operations on feature information and to enhance the model’s capability to extract features from low-resolution and small targets. Second, a coordinate attention mechanism was added after the convolution operation to improve model detection accuracy with small targets under image blurring. Third, the nearest-neighbor interpolation in the original network upsampling was replaced with transposed convolution to increase the receptive field range of the neck and reduce detail loss. Finally, the CIoU loss function was replaced with the Alpha-IoU loss function to solve the problem of the slow convergence of gradients during training on small target images. Using the images of Artemisia salina, taken in Hunshandake sandy land in China, as a dataset, the experimental results demonstrated that the proposed algorithm provides significantly improved results (average precision = 80.17%, accuracy = 73.45% and recall rate = 76.97%, i.e., improvements by 14.96%, 6.24%, and 7.21%, respectively, compared with the original model) and also outperforms other detection algorithms. The detection of small objects and blurry images has been significantly improved.
    Type of Medium: Online Resource
    ISSN: 2076-3417
    URL: Article
    DOI: 10.3390/app13095409
    Language: English
    Publisher: MDPI AG
    Publication Date: 2023
    detail.hit.zdb_id: 2704225-X
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  • 3
    Online Resource
    Online Resource
    Design and Ground Performance Evaluation of a Multi-Joint Wheel-Track Composite Mobile Robot for Enhanced Terrain Adaptability
    MDPI AG ; 2023
    In:  Applied Sciences Vol. 13, No. 12 ( 2023-06-18), p. 7270-
    Details
    In: Applied Sciences, MDPI AG, Vol. 13, No. 12 ( 2023-06-18), p. 7270-
    Abstract: The tracked-wheeled mobile robot has gained significant attention in military, agricultural, construction, and other fields due to its exceptional mobility and off-road capabilities. Therefore, it is an ideal choice for reconnaissance and exploration tasks. In this study, we proposed a multi-jointed tracked-wheeled compound mobile robot that can overcome various terrains and obstacles. Based on the characteristics of multi-jointed robots, we designed two locomotion modes for the robot to climb stairs and established the kinematics/dynamics equations for its land movement. We evaluated the robot’s stability during slope climbing, its static stability during stair climbing, and its ability to cross trenches. Based on our evaluation results, we determined the key conditions for the robot to overcome obstacles, the maximum height it can climb stairs, and the maximum width it can cross trenches. Additionally, we developed a simulation model to verify the robot’s performance in different terrains and the reliability of its stair-climbing gait. The simulation results demonstrate that our multi-jointed tracked-wheeled compound mobile robot exhibits excellent reliability and adaptability in complex terrain, indicating broad application prospects in various fields and space missions.
    Type of Medium: Online Resource
    ISSN: 2076-3417
    URL: Article
    DOI: 10.3390/app13127270
    Language: English
    Publisher: MDPI AG
    Publication Date: 2023
    detail.hit.zdb_id: 2704225-X
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  • 4
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    Tribological Performance of MoS2–WS2 Composite Film under the Atomic Oxygen Irradiation Conditions
    MDPI AG ; 2020
    In:  Materials Vol. 13, No. 6 ( 2020-03-19), p. 1407-
    Details
    In: Materials, MDPI AG, Vol. 13, No. 6 ( 2020-03-19), p. 1407-
    Abstract: The oxidation and erosion of atomic oxygen are considered to be the most dangerous environmental factors for materials exposed to the aerospace environment. In order to investigate the effect of atomic oxygen on the lubricating film and improve the tribological properties, MoS2–WS2 composite film was prepared by the sputtering technique. The film structure and mechanical behavior were characterized and their vacuum tribological properties were evaluated by a friction tester. The composite film possessed better atomic oxygen (AO) resistance than pure film because of the dense structure. The tribological performance of composite film was different under the conditions after AO-irradiation and sliding and during AO-irradiation. After AO-irradiation, the tribological properties of composite film were similar to those before AO-irradiation. However, high friction noise, wear rate, and reduced wear duration were observed for the composite film under the AO-irradiation/friction process because of the continuous damage of the lubricating film due to the AO-irradiation. The addition of 16 at.% WS2 to the MoS2-based film changed the composite film structure and improved the oxidation resistance of the film, making the composite film exhibit better tribological performance than pure MoS2.
    Type of Medium: Online Resource
    ISSN: 1996-1944
    URL: Article
    DOI: 10.3390/ma13061407
    Language: English
    Publisher: MDPI AG
    Publication Date: 2020
    detail.hit.zdb_id: 2487261-1
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  • 5
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    CO2 Absorption Mechanism by the Deep Eutectic Solvents Formed by Monoethanolamine-Based Protic Ionic Liquid and Ethylene Glycol
    MDPI AG ; 2022
    In:  International Journal of Molecular Sciences Vol. 23, No. 3 ( 2022-02-08), p. 1893-
    Details
    In: International Journal of Molecular Sciences, MDPI AG, Vol. 23, No. 3 ( 2022-02-08), p. 1893-
    Abstract: Deep eutectic solvents (DESs) have been widely used to capture CO2 in recent years. Understanding CO2 mechanisms by DESs is crucial to the design of efficient DESs for carbon capture. In this work, we studied the CO2 absorption mechanism by DESs based on ethylene glycol (EG) and protic ionic liquid ([MEAH][Im] ), formed by monoethanolamine (MEA) with imidazole (Im). The interactions between CO2 and DESs [MEAH][Im] -EG (1:3) are investigated thoroughly by applying 1H and 13 C nuclear magnetic resonance (NMR), 2-D NMR, and Fourier-transform infrared (FTIR) techniques. Surprisingly, the results indicate that CO2 not only binds to the amine group of MEA but also reacts with the deprotonated EG, yielding carbamate and carbonate species, respectively. The reaction mechanism between CO2 and DESs is proposed, which includes two pathways. One pathway is the deprotonation of the [MEAH]+ cation by the [Im] − anion, resulting in the formation of neutral molecule MEA, which then reacts with CO2 to form a carbamate species. In the other pathway, EG is deprotonated by the [Im]−, and then the deprotonated EG, HO-CH2-CH2-O−, binds with CO2 to form a carbonate species. The absorption mechanism found by this work is different from those of other DESs formed by protic ionic liquids and EG, and we believe the new insights into the interactions between CO2 and DESs will be beneficial to the design and applications of DESs for carbon capture in the future.
    Type of Medium: Online Resource
    ISSN: 1422-0067
    URL: Article
    DOI: 10.3390/ijms23031893
    Language: English
    Publisher: MDPI AG
    Publication Date: 2022
    detail.hit.zdb_id: 2019364-6
    SSG: 12
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  • 6
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    Hyperspectral Target Detection with an Auxiliary Generative Adversarial Network
    MDPI AG ; 2021
    In:  Remote Sensing Vol. 13, No. 21 ( 2021-11-05), p. 4454-
    Details
    In: Remote Sensing, MDPI AG, Vol. 13, No. 21 ( 2021-11-05), p. 4454-
    Abstract: In recent years, the deep neural network has shown a strong presence in classification tasks and its effectiveness has been well proved. However, the framework of DNN usually requires a large number of samples. Compared to the training sets in classification tasks, the training sets for the target detection of hyperspectral images may only include a few target spectra which are quite limited and precious. The insufficient labeled samples make the DNN-based hyperspectral target detection task a challenging problem. To address this problem, we propose a hyperspectral target detection approach with an auxiliary generative adversarial network. Specifically, the training set is first expanded by generating simulated target spectra and background spectra using the generative adversarial network. Then, a classifier which is highly associated with the discriminator of the generative adversarial network is trained based on the real and the generated spectra. Finally, in order to further suppress the background, guided filters are utilized to improve the smoothness and robustness of the detection results. Experiments conducted on real hyperspectral images show the proposed approach is able to perform more efficiently and accurately compared to other target detection approaches.
    Type of Medium: Online Resource
    ISSN: 2072-4292
    URL: Article
    DOI: 10.3390/rs13214454
    Language: English
    Publisher: MDPI AG
    Publication Date: 2021
    detail.hit.zdb_id: 2513863-7
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  • 7
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    Dual-Weighted Kernel Extreme Learning Machine for Hyperspectral Imagery Classification
    MDPI AG ; 2021
    In:  Remote Sensing Vol. 13, No. 3 ( 2021-02-01), p. 508-
    Details
    In: Remote Sensing, MDPI AG, Vol. 13, No. 3 ( 2021-02-01), p. 508-
    Abstract: Due to its excellent performance in high-dimensional space, the kernel extreme learning machine has been widely used in pattern recognition and machine learning fields. In this paper, we propose a dual-weighted kernel extreme learning machine for hyperspectral imagery classification. First, diverse spatial features are extracted by guided filtering. Then, the spatial features and spectral features are composited by a weighted kernel summation form. Finally, the weighted extreme learning machine is employed for the hyperspectral imagery classification task. This dual-weighted framework guarantees that the subtle spatial features are extracted, while the importance of minority samples is emphasized. Experiments carried on three public data sets demonstrate that the proposed dual-weighted kernel extreme learning machine (DW-KELM) performs better than other kernel methods, in terms of accuracy of classification, and can achieve satisfactory results.
    Type of Medium: Online Resource
    ISSN: 2072-4292
    URL: Article
    DOI: 10.3390/rs13030508
    Language: English
    Publisher: MDPI AG
    Publication Date: 2021
    detail.hit.zdb_id: 2513863-7
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  • 8
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    3D Reconstruction of High Reflective Welding Surface Based on Binocular Structured Light Stereo Vision
    MDPI AG ; 2022
    In:  Machines Vol. 10, No. 2 ( 2022-02-20), p. 159-
    Details
    In: Machines, MDPI AG, Vol. 10, No. 2 ( 2022-02-20), p. 159-
    Abstract: The inspection of welding surface quality is an important task for welding work. With the development of product quality inspection technology, automated and machine vision-based inspection have been applied to more industrial application fields because of its non-contact, convenience, and high efficiency. However, challenging material and optical phenomena such as high reflective surface areas often present on welding seams tend to produce artifacts such as holes in the reconstructed model using current visual sensors, hence leading to insufficiency or even errors in the inspection result. This paper presents a 3D reconstruction technique for highly reflective welding surfaces based on binocular style structured light stereo vision. The method starts from capturing a fully lit image for identifying highly reflective regions on a welding surface using conventional computer vision models, including gray-scale, binarization, dilation, and erosion. Then, fringe projection profilometry is used to generate point clouds on the interested area. The mapping and alignment from 2D image to 3D point cloud is then established to highlight features that are vital for eliminating “holes”—large featureless areas—caused by high reflections such as the specular mirroring effect. A two-way slicing method is proposed to operate on the refined point cloud, following the concept of dimensionality reduction to project the sliced point cloud onto different image planes before a Smoothing Spline model is applied to fit the discrete point formed by projection. The 3D coordinate values of points in the “hole” region are estimated according to the fitted curves and appended to the original point cloud using iterative algorithms. Experiment results verify that the proposed method can accurately reconstruct a wide range of welding surfaces with significantly improved precision.
    Type of Medium: Online Resource
    ISSN: 2075-1702
    URL: Article
    DOI: 10.3390/machines10020159
    Language: English
    Publisher: MDPI AG
    Publication Date: 2022
    detail.hit.zdb_id: 2704328-9
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  • 9
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    Iron-Based Composite Oxide Catalysts Tuned by CTAB Exhibit Superior NH3–SCR Performance
    MDPI AG ; 2021
    In:  Catalysts Vol. 11, No. 2 ( 2021-02-08), p. 224-
    Details
    In: Catalysts, MDPI AG, Vol. 11, No. 2 ( 2021-02-08), p. 224-
    Abstract: Iron-based oxide catalysts for the NH3–SCR (selective catalytic reduction of NOx by NH3) reaction have gained attention due to their high catalytic activity and structural adjustability. In this work, iron–niobium, iron–titanate and iron–molybdenum composite oxides were synthesized by a co-precipitation method with or without the assistance of hexadecyl trimethyl ammonium bromide (CTAB). The catalysts synthesized with the assistance of CTAB (FeM0.3Ox-C, M = Nb, Ti, Mo) showed superior SCR performance in an operating temperature range from 150 °C to 400 °C compared to those without CTAB addition (FeM0.3Ox, M = Nb, Ti, Mo). To reveal such enhancement, the catalysts were characterized by N2-physisorption, XRD (Powder X-ray diffraction), NH3-TPD (temperature-programmed desorption of ammonia), DRIFTS (Diffuse Reflectance Infrared Fourier Transform Spectroscopy), XPS (X-ray Photoelectron Spectroscopy), and H2-TPR (H2-Total Physical Response). It was found that the crystalline phase of Fe2O3 formed was influenced by the presence of CTAB in the preparation process, which favored the formation of crystalline γ-Fe2O3. Owing to the changed structure, the redox-acid properties of FeM0.3Ox-C catalysts were modified, with higher exposure of acid sites and improved ability of NO oxidation to NO2 at low-temperature, both of which also contributed to the improvement of NOx conversion. In addition, the weakened redox ability of Fe prevented the over-oxidation of NH3, thus accounting for the greatly improved high-temperature activity as well as N2 selectivity.
    Type of Medium: Online Resource
    ISSN: 2073-4344
    URL: Article
    DOI: 10.3390/catal11020224
    Language: English
    Publisher: MDPI AG
    Publication Date: 2021
    detail.hit.zdb_id: 2662126-5
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  • 10
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    In Vivo Production of HN Protein Increases the Protection Rates of a Minicircle DNA Vaccine against Genotype VII Newcastle Disease Virus
    MDPI AG ; 2021
    In:  Vaccines Vol. 9, No. 7 ( 2021-07-02), p. 723-
    Details
    In: Vaccines, MDPI AG, Vol. 9, No. 7 ( 2021-07-02), p. 723-
    Abstract: The Cre-recombinase mediated in vivo minicircle DNA vaccine platform (CRIM) provided a novel option to replace a traditional DNA vaccine. To further improve the immune response of our CRIM vaccine, we designed a dual promoter expression plasmid named pYL87 which could synthesize short HN protein under a prokaryotic in vivo promoter PpagC and full length HN protein of genotype VII Newcastle disease virus (NDV) under the previous eukaryotic CMV promoter at the same time. Making use of the self-lysed Salmonella strain as a delivery vesicle, chickens immunized with the pYL87 construction showed an increased serum haemagglutination inhibition antibody response, as well as an increased cell proliferation level and cellular IL-4 and IL-18 cytokines, compared with the previous CRIM vector pYL47. After the virus challenge, the pYL87 vector could provide 80% protection compared to 50% protection against genotype VII NDV in pYL47 immunized chickens, indicating a promising dual promoter strategy used in vaccine design.
    Type of Medium: Online Resource
    ISSN: 2076-393X
    URL: Article
    DOI: 10.3390/vaccines9070723
    Language: English
    Publisher: MDPI AG
    Publication Date: 2021
    detail.hit.zdb_id: 2703319-3
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