Counting Crowds in Bad Weather

Crowd counting has recently attracted significant attention in the field of computer vision due to its wide applications to image understanding. Numerous methods have been proposed and achieved state-of-the-art performance for real-world tasks. However, existing approaches do not perform well under adverse weather such as haze, rain, and snow since the visual appearances of crowds in such scenes are drastically different from those images in clear weather of typical datasets. In this paper, we propose a method for robust crowd counting in adverse weather scenarios. Instead of using a two-stage approach that involves image restoration and crowd counting modules, our model learns effective features and adaptive queries to account for large appearance variations. With these weather queries, the proposed model can learn the weather information according to the degradation of the input image and optimize with the crowd counting module simultaneously. Experimental results show that the proposed algorithm is effective in counting crowds under different weather types on benchmark datasets. The source code and trained models will be made available to the public.Comment: including supplemental materia

Comparison of extracorporeal shock wave lithotripsy running models between outsourcing cooperation and rental cooperation conducted in Taiwan

Background/PurposeWe conducted a retrospective study to compare the cost and effectiveness between two different running models for extracorporeal shock wave lithotripsy (SWL), including the outsourcing cooperation model (OC) and the rental cooperation model (RC).MethodsBetween January 1999 and December 2005, we implemented OC for the SWL, and from January 2006 to October 2011, RC was utilized. With OC, the cooperative company provided a machine and shared a variable payment with the hospital, according to treatment sessions. With RC, the cooperative company provided a machine and received a fixed rent from the hospital. We calculated the cost of each treatment session, and evaluated the break-even point to estimate the lowest number of treatment sessions to make the balance between revenue and cost every month. Effectiveness parameters, including the stone-free rate, the retreatment rate, the rate of additional procedures and complications, were evaluated.ResultsCompared with OC there were significantly less treatment sessions for RC every month (42.6±7.8 vs. 36.8±6.5, p=0.01). The cost of each treatment session was significantly higher for OC than for RC (751.6±20.0 USD vs. 684.7±16.7 USD, p=0.01). The break-even point for the hospital was 27.5 treatment sessions/month for OC, when the hospital obtained 40% of the payment, and it could be reduced if the hospital got a greater percentage. The break-even point for the hospital was 27.3 treatment sessions/month for RC. No significant differences were noticed for the stone-free rate, the retreatment rate, the rate of additional procedures and complications.ConclusionOur study revealed that RC had a lower cost for every treatment session, and fewer treatment sessions of SWL/month than OC. The study might provide a managerial implication for healthcare organization managers, when they face a situation of high price equipment investment

Deploying Image Deblurring across Mobile Devices: A Perspective of Quality and Latency

Recently, image enhancement and restoration have become important applications on mobile devices, such as super-resolution and image deblurring. However, most state-of-the-art networks present extremely high computational complexity. This makes them difficult to be deployed on mobile devices with acceptable latency. Moreover, when deploying to different mobile devices, there is a large latency variation due to the difference and limitation of deep learning accelerators on mobile devices. In this paper, we conduct a search of portable network architectures for better quality-latency trade-off across mobile devices. We further present the effectiveness of widely used network optimizations for image deblurring task. This paper provides comprehensive experiments and comparisons to uncover the in-depth analysis for both latency and image quality. Through all the above works, we demonstrate the successful deployment of image deblurring application on mobile devices with the acceleration of deep learning accelerators. To the best of our knowledge, this is the first paper that addresses all the deployment issues of image deblurring task across mobile devices. This paper provides practical deployment-guidelines, and is adopted by the championship-winning team in NTIRE 2020 Image Deblurring Challenge on Smartphone Track.Comment: CVPR 2020 Workshop on New Trends in Image Restoration and Enhancement (NTIRE

AMiBA Wideband Analog Correlator

A wideband analog correlator has been constructed for the Yuan-Tseh Lee Array for Microwave Background Anisotropy. Lag correlators using analog multipliers provide large bandwidth and moderate frequency resolution. Broadband IF distribution, backend signal processing and control are described. Operating conditions for optimum sensitivity and linearity are discussed. From observations, a large effective bandwidth of around 10 GHz has been shown to provide sufficient sensitivity for detecting cosmic microwave background variations.Comment: 28 pages, 23 figures, ApJ in press

Sequence Variants of ADIPOQ

Diabetes is a serious global health problem. Large-scale genome-wide association studies identified loci for type 2 diabetes mellitus (T2DM), including adiponectin (ADIPOQ) gene and transcription factor 7-like 2 (TCF7L2), but few studies clarified the effect of genetic polymorphisms of ADIPOQ and TCF7L2 on risk of T2DM. We attempted to elucidate association between T2DM and polymorphic variations of both in Taiwan’s Chinese Han population, with our retrospective case-control study genotyping single nucleotide polymorphisms (SNPs) in ADIPOQ and TCF7L2 genes both in 149 T2DM patients and in 139 healthy controls from Taiwan. Statistical analysis gauged association of these polymorphisms with risk of T2DM to show ADIPOQ rs1501299 polymorphism variations strongly correlated with T2DM risk (P=0.042), with rs2241766 polymorphism being not associated with T2DM (P=0.967). However, both polymorphisms rs7903146 and rs12255372 of TCF7L2 were rarely detected in Taiwanese people. This study avers that ADIPOQ rs1501299 polymorphism contributes to risk of T2DM in the Taiwanese population

AMiBA: scaling relations between the integrated Compton-y and X-ray derived temperature, mass, and luminosity

We investigate the scaling relations between the X-ray and the thermal Sunyaev-Zel'dovich Effect (SZE) properties of clusters of galaxies, using data taken during 2007 by the Y.T. Lee Array for Microwave Background Anisotropy (AMiBA) at 94 GHz for the six clusters A1689, A1995, A2142, A2163, A2261, and A2390. The scaling relations relate the integrated Compton-y parameter Y_{2500} to the X-ray derived gas temperature T_{e}, total mass M_{2500}, and bolometric luminosity L_X within r_{2500}. Our results for the power-law index and normalization are both consistent with the self-similar model and other studies in the literature except for the Y_{2500}-L_X relation, for which a physical explanation is given though further investigation may be still needed. Our results not only provide confidence for the AMiBA project but also support our understanding of galaxy clusters.Comment: Accepted by ApJ; 8 pages, 3 figures, 5 table

KCNN2 polymorphisms and cardiac tachyarrhythmias

Potassium calcium-activated channel subfamily N member 2 (KCNN2) encodes an integral membrane protein that forms small-conductance calcium-activated potassium (SK) channels. Recent studies in animal models show that SK channels are important in atrial and ventricular repolarization and arrhythmogenesis. However, the importance of SK channels in human arrhythmia remains unclear. The purpose of the present study was to test the association between genetic polymorphism of the SK2 channel and the occurrence of cardiac tachyarrhythmias in humans. We enrolled 327 Han Chinese, including 72 with clinically significant ventricular tachyarrhythmias (VTa) who had a history of aborted sudden cardiac death (SCD) or unexplained syncope, 98 with a history of atrial fibrillation (AF), and 144 normal controls. We genotyped 12 representative tag single nucleotide polymorphisms (SNPs) across a 141-kb genetic region containing the KCNN2 gene; these captured the full haplotype information. The rs13184658 and rs10076582 variants of KCNN2 were associated with VTa in both the additive and dominant models (odds ratio [OR] 2.89, 95% confidence interval [CI] = 1.505-5.545, P = 0.001; and OR 2.55, 95% CI = 1.428-4.566, P = 0.002, respectively). After adjustment for potential risk factors, the association remained significant. The population attributable risks of these 2 variants of VTa were 17.3% and 10.6%, respectively. One variant (rs13184658) showed weak but significant association with AF in a dominant model (OR 1.91, CI = 1.025-3.570], P = 0.042). There was a significant association between the KCNN2 variants and clinically significant VTa. These findings suggest an association between KCNN2 and VTa; it also appears that KCNN2 variants may be adjunctive markers for risk stratification in patients susceptible to SCD