25,690 research outputs found
Cissampelos keniensis Y. D. Zhou & Q. F. Wang
No full textE Cissampelos keniensis Y.D.Zhou & Q.F.Wang — Habit: Liana. Habitat: LMWF; 2 000–2 300 m. Distribution: IIIc. Voucher: Kaburia Track, Alt. 2 241 m, 29 Jun. 2016, Zhou & Mbuni 16/14 (HIB, EA, PE). Reference: Zhou et al. (2017b).Published as part of Zhou, Ya-Dong, Mwachala, Geoffrey, Hu, Guang-Wan & Wang, Qing-Feng, 2022, Annotated checklist of the vascular plants of Mount Kenya, East Africa, pp. 1-108 in Phytotaxa 546 (1) on page 41, DOI: 10.11646/phytotaxa.546.1.1, http://zenodo.org/record/655046
Zehneria subcoriacea Y. D. Zhou & Q. F. Wang
No full textZehneria subcoriacea Y.D.Zhou & Q.F.Wang — Habit: Climber. Habitat: LMWF, BZ, UMF; 2 000–3 200 m. Distribution: IIIa. Voucher: Naro Moru Track, near Met. Station, Alt. 3065 m, 27 Jun. 2016, Zhou & Mbuni 16/3 (HIB, EA, PE). Reference: Zhou et al. (2016b).Published as part of Zhou, Ya-Dong, Mwachala, Geoffrey, Hu, Guang-Wan & Wang, Qing-Feng, 2022, Annotated checklist of the vascular plants of Mount Kenya, East Africa, pp. 1-108 in Phytotaxa 546 (1) on page 52, DOI: 10.11646/phytotaxa.546.1.1, http://zenodo.org/record/655046
Association between Wind Environment and Spatial Characteristics of High-Rise Residential Buildings in Cold Regions through Field Measurements in Xi’an
No full textResearch on the correlation between wind and block spatial form focuses mainly on hot and humid cities. However, cold regions are also experiencing high summer temperatures due to global climate change. Enhancing wind speed in blocks through urban spatial control improves comfort. Existing research cannot be directly applied to cold regions due to natural differences. Using Xi’an as an example, this study explores the impact of high-rise residential block spatial form on internal and external wind environments through field measurements and simulations. Optimal strategies for block planning and architectural design are identified to improve the wind environment. Results show that blocks with high buildings on the south and north sides and low buildings in the middle achieve a more comfortable internal wind environment. Gradually increasing building height from south to north has minimal impact on downwind blocks. Reducing the angle between the main facade and dominant wind direction enhances the residential area’s wind environment. Specific spatial planning and design strategies are summarized for early-stage decision-making
d-q axis current waveform when the motor starts.
No full textd-q axis current waveform when the motor starts.</p
d-q axis current waveform when the given speed changes.
No full textd-q axis current waveform when the given speed changes.</p
Gradient Feature-Oriented 3-D Domain Adaptation for Hyperspectral Image Classification
No full textDomain adaptation, which cleverly applies the classifier learned from the source domain with sufficient labeled samples to the target domain with limited labeled samples, provides a feasible alternative to handle the small training sample problem of hyperspectral image (HSI) classification and has attracted much attention in the research field recently. Apparently, feature discriminative ability is vital for domain adaptation, which plays a crucial role during the migration process of transfer learning. In this article, a gradient feature-oriented 3-D domain adaptation (GF-3DDA) approach is proposed for HSI classification. First, 3-D Gabor is employed to remove noise from the original data, and two 2-D gradient-based features, 2-D Sobel gradient (SG) and 2-D derivative-of-Gaussian (DtG), are extended to the 3-D domain to coincide with the integrated spatial-spectral organization of HSI. Thus, the 3-D Sobel-Gabor gradient (3DSGG) and 3-D derivative-of-Gaussian-Gabor (3DDGG) features are achieved. Second, a 3-D domain adaptation method is implemented to jointly exploit the second- and fourth-order statistical descriptors in the spatial-spectral dimensions, which could effectively reduce domain shifts and thus achieve improved domain adaptation. Third, all the extracted domain-adapted feature modules are collaboratively classified by extreme learning machine (ELM), and the probability-like outputs of every ELM classifier are combined together to accomplish the classification task. Four hyperspectral data sets that each contains two scenes, i.e., Pavia, Shanghai-Hangzhou, Indiana, and Houston, are tested in the experiments. When only ten labeled samples per class are used in the target domain, the classification accuracies on four hyperspectral data sets achieved by our GF-3DDA approach are 93.31%, 84.35%, 69.32%, and 80.06%, respectively.No Full Tex
Modeling Fuel-Air Mixing, Combustion and Soot Formation with Ducted Fuel Injection Using Tabulated Kinetics
No full textDucted Fuel Injection (DFI) has the potential to reduce soot emissions in Diesel engines thanks to the enhanced mixing rate resulting from the liquid fuel flow through a small cylindrical pipe located at a certain distance from the nozzle injector hole. A consolidated set of experiments in constant-volume vessel and engine allowed to understand the effects of ambient conditions, duct geometry and shape on fuel-air mixing, combustion and soot formation. However, implementation of this promising technology in compression-ignition engines requires predictive numerical models that can properly support the design of combustion systems in a wide range of operating conditions. This work presents a computational methodology to predict fuel-air mixing and combustion with ducted fuel injection. Attention is mainly focused on turbulence and combustion modelling. The first is mainly responsible for the mixture formation process in presence of large velocity gradients and flow recirculations, while the second must include detailed kinetics and turbulence chemistry-interaction to correctly predict ignition delay and flame structure. Literature experimental data were used for model assessment and validation under different ambient conditions considering both free-spray and ducted fuel injection configurations. Two different RANS turbulence models were tested (k - ? and k- ? -SST) to evaluate how they describe the flow in the duct region and the air/fuel mixing occurring downstream. Afterwards, combustion simulations were carried out using a tabulated flamelet progress variable model based on auto-ignition calculations of diffusion flames using detailed kinetics. Experimental data of ignition delay, flame lift-off and soot mass evolution were used to validate the proposed approach
Sedum keniense Y. D. Zhou, G. W. Hu & Q. F. Wang
No full textE Sedum keniense Y.D.Zhou, G.W.Hu & Q.F.Wang — Habit: Herb. Habitat: HZ; 3 000–3 200 m. Distribution: IIIc. Voucher: Chogoria Waterfall, Alt. 3 184 m, 25 Jan. 2015, SAJIT 002822 (HIB, PE, EA). Reference: Zhou et al. (2016a).Published as part of Zhou, Ya-Dong, Mwachala, Geoffrey, Hu, Guang-Wan & Wang, Qing-Feng, 2022, Annotated checklist of the vascular plants of Mount Kenya, East Africa, pp. 1-108 in Phytotaxa 546 (1) on page 43, DOI: 10.11646/phytotaxa.546.1.1, http://zenodo.org/record/655046
BPNN-Based Real-Time Recognition of Locomotion Modes for an Active Pelvis Orthosis with Different Assistive Strategies
No full textReal-time human intent recognition is important for controlling low-limb wearable robots. In this paper, to achieve continuous and precise recognition results on different terrains, we propose a real-time training and recognition method for six locomotion modes including standing, level ground walking, ramp ascending, ramp descending, stair ascending and stair descending. A locomotion recognition system is designed for the real-time recognition purpose with an embedded BPNN-based algorithm. A wearable powered orthosis integrated with this system and two inertial measurement units is used as the experimental setup to evaluate the performance of the designed method while providing hip assistance. Experiments including on-board training and real-time recognition parts are carried out on three able-bodied subjects. The overall recognition accuracies of six locomotion modes based on subject-dependent models are 98.43% and 98.03% respectively, with the wearable orthosis in two different assistance strategies. The cost time of recognition decision delivered to the orthosis is about 0.9ms. Experimental results show an effective and promising performance of the proposed method to realize real-time training and recognition for future control of low-limb wearable robots assisting users on different terrains
Associations between summer wind environment and urban physical indicators in commercial blocks based on field measurement and simulation in Xi'an
No full textAs a major driving force to improve economic output, commercial blocks also play a significant role in enhancing urban vitality. Due to its characteristics of high building density and large building volume, many wind environment problems are likely to appear in commercial blocks. In this research, we simulated the wind environment of four theoretical block models and real commercial blocks in STREAM software. The results suggest that under the same other conditions, the wind speed inside the block is the lowest when its building footprint ratio reaches about 56%. When the building footprint ratio is greater than 56.3% and gradually increasing, or less than 39.1% and gradually decreasing, the wind speed both inside and around the block will be steadily increased. In addition, we also found the quantitative correlations between the wind environment and other urban physical indicators, such as mean building height, stagger ratio of building height and enclosure degree, according to which we proposed the adjustment strategies of the spatial form of commercial blocks. Finally, we used four cases to verify the effectiveness of these strategies in optimizing the wind environment of commercial blocks
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