1,214 research outputs found
Pablo & The Artists: a mobile game for art education
Pablo & The Artists is an educational mobile application project. This documentation aims to focus and further explore the opportunities of a mobile application by analysing the process of Pablo & The Artists. My emphasis is on the design aspect of creating a mobile gaming experience, involving researches on user behaviors of a particular group and technical implementations of a complex mobile application
ED-Dehaze Net: Encoder and Decoder Dehaze Network.
The presence of haze will significantly reduce the quality of images, such as resulting in lower contrast and blurry details. This paper proposes a novel end-to-end dehazing method, called Encoder and Decoder Dehaze Network (ED-Dehaze Net), which contains a Generator and a Discriminator. In particular, the Generator uses an Encoder-Decoder structure to effectively extract the texture and semantic features of hazy images. Between the Encoder and Decoder we use Multi-Scale Convolution Block (MSCB) to enhance the process of feature extraction. The proposed ED-Dehaze Net is trained by combining Adversarial Loss, Perceptual Loss and Smooth L1 Loss. Quantitative and qualitative experimental results showed that our method can obtain the state-of-the-art dehazing performance
ED-Dehaze Net: Encoder and Decoder Dehaze Network
The presence of haze will significantly reduce the quality of images, such as resulting in lower contrast and blurry details. This paper proposes a novel end-to-end dehazing method, called Encoder and Decoder Dehaze Network (ED-Dehaze Net), which contains a Generator and a Discriminator. In particular, the Generator uses an Encoder-Decoder structure to effectively extract the texture and semantic features of hazy images. Between the Encoder and Decoder we use Multi-Scale Convolution Block (MSCB) to enhance the process of feature extraction. The proposed ED-Dehaze Net is trained by combining Adversarial Loss, Perceptual Loss and Smooth L1 Loss. Quantitative and qualitative experimental results showed that our method can obtain the state-of-the-art dehazing performance
Dual-attention Focused Module for Weakly Supervised Object Localization
The research on recognizing the most discriminative regions provides
referential information for weakly supervised object localization with only
image-level annotations. However, the most discriminative regions usually
conceal the other parts of the object, thereby impeding entire object
recognition and localization. To tackle this problem, the Dual-attention
Focused Module (DFM) is proposed to enhance object localization performance.
Specifically, we present a dual attention module for information fusion,
consisting of a position branch and a channel one. In each branch, the input
feature map is deduced into an enhancement map and a mask map, thereby
highlighting the most discriminative parts or hiding them. For the position
mask map, we introduce a focused matrix to enhance it, which utilizes the
principle that the pixels of an object are continuous. Between these two
branches, the enhancement map is integrated with the mask map, aiming at
partially compensating the lost information and diversifies the features. With
the dual-attention module and focused matrix, the entire object region could be
precisely recognized with implicit information. We demonstrate outperforming
results of DFM in experiments. In particular, DFM achieves state-of-the-art
performance in localization accuracy in ILSVRC 2016 and CUB-200-2011.Comment: 8 pages, 6 figures and 4 table
Label-Free Liver Tumor Segmentation
We demonstrate that AI models can accurately segment liver tumors without the
need for manual annotation by using synthetic tumors in CT scans. Our synthetic
tumors have two intriguing advantages: (I) realistic in shape and texture,
which even medical professionals can confuse with real tumors; (II) effective
for training AI models, which can perform liver tumor segmentation similarly to
the model trained on real tumors -- this result is exciting because no existing
work, using synthetic tumors only, has thus far reached a similar or even close
performance to real tumors. This result also implies that manual efforts for
annotating tumors voxel by voxel (which took years to create) can be
significantly reduced in the future. Moreover, our synthetic tumors can
automatically generate many examples of small (or even tiny) synthetic tumors
and have the potential to improve the success rate of detecting small liver
tumors, which is critical for detecting the early stages of cancer. In addition
to enriching the training data, our synthesizing strategy also enables us to
rigorously assess the AI robustness.Comment: CVPR 202
The Effect of 6-Week Combined Balance and Plyometric Training on Change of Direction Performance of Elite Badminton Players
The study aimed to investigate the effect of combined balance and plyometric training on the change of direction (COD) performance of badminton athletes. Sixteen elite male badminton players volunteered to participate and were randomly assigned to a balance-plyometric group (BP: n = 8) and plyometric group (PL: n = 8). The BP group performed balance combined with plyometric training three times a week over 6 weeks; while the PL group undertook only plyometric training three times a week during the same period. Meanwhile, both groups were given the same technical training. All participants were tested to assess the COD ability before and after the training period: Southeast Missouri (SEMO) test and 5-0-5 test, dynamic balance ability (Y-Balance test, YBT), and reactive strength index (RSI). Repeated-measure ANOVA revealed that after the intervention there was a significant time × group interaction for 5-0-5 COD test, YBT of both legs and RSI (p < 0.05, partial η2 = 0.26–0.58) due to the better performance observed at post-test compared with a pre-test for the BP group [effect size (ES) = 1.20–1.76], and the improvement was higher than that of the PL group. The change in SEMO test did not differ between BP and PL (p < 0.159, partial η2= 0.137), but the magnitude of the with-group improvement for BP (ES = 1.55) was higher than that of PL (ES = 0.81). These findings suggest that combined training could further improve the COD performance of badminton athletes than plyometric training alone and might provide fitness trainers a more efficient COD training alternative
High Genetic Diversity of HIV-1 and Active Transmission Clusters among Male-to-Male Sexual Contacts (MMSCs) in Zhuhai, China
Monitoring genetic diversity and recent HIV infections (RHIs) is critical for understanding HIV epidemiology. Here, we report HIV-1 genetic diversity and RHIs in blood samples from 190 HIV-positive MMSCs in Zhuhai, China. MMSCs with newly reported HIV were enrolled from January 2020 to June 2022. A nested PCR was performed to amplify the HIV polymerase gene fragments at HXB2 positions 2604–3606. We constructed genetic transmission network at both 0.5% and 1.5% distance thresholds using the Tamura-Nei93 model. RHIs were identified using a recent infection testing algorithm (RITA) combining limiting antigen avidity enzyme immunoassay (LAg-EIA) assay with clinical data. The results revealed that 19.5% (37/190) were RHIs and 48.4% (92/190) were CRF07_BC. Two clusters were identified at a 0.5% distance threshold. Among them, one was infected with CRF07_BC for the long term, and the other was infected with CRF55_01B recently. We identified a total of 15 clusters at a 1.5% distance threshold. Among them, nine were infected with CRF07_BC subtype, and RHIs were found in 38.8% (19/49) distributed in eight genetic clusters. We identified a large active transmission cluster (n = 10) infected with a genetic variant, CRF79_0107. The multivariable logistic regression model showed that clusters were more likely to be RHIs (adjusted OR: 3.64, 95% CI: 1.51~9.01). The RHI algorithm can help to identify recent or ongoing transmission clusters where the prevention tools are mostly needed. Prompt public health measures are needed to contain the further spread of active transmission clusters
Surface skyrmions and dual topological Hall effect in antiferromagnetic topological insulator EuCdAs
In this work, we synthesized single crystal of EuCdAs, which exhibits
A-type antiferromagnetic (AFM) order with in-plane spin orientation below
= 9.5~K.Optical spectroscopy and transport measurements suggest its topological
insulator (TI) nature with an insulating gap around 0.1eV. Remarkably, a dual
topological Hall resistivity that exhibits same magnitude but opposite signs in
the positive to negative and negative to positive magnetic field hysteresis
branches emerges below 20~K. With magnetic force microscopy (MFM) images and
numerical simulations, we attribute the dual topological Hall effect to the
N\'{e}el-type skyrmions stabilized by the interactions between topological
surface states and magnetism, and the sign reversal in different hysteresis
branches indicates potential coexistence of skyrmions and antiskyrmions. Our
work uncovers a unique two-dimensional (2D) magnetism on the surface of
intrinsic AFM TI, providing a promising platform for novel topological quantum
states and AFM spintronic applications.Comment: 7 pages, 3 figure
Healthy cities initiative in China: Progress, challenges, and the way forward
Article discusses how China implemented the first phase of its National Healthy Cities pilot program from 2016-20. Authors recommend aligning the Healthy Cities initiative in China with strategic national and global level agendas such as Healthy China 2030 and the Sustainable Development Goals (SDGs) by providing an integrative governance framework to facilitate a coherent intersectoral program to systemically improve population health
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