SCNet: Learning Semantic Correspondence

This paper addresses the problem of establishing semantic correspondences between images depicting different instances of the same object or scene category. Previous approaches focus on either combining a spatial regularizer with hand-crafted features, or learning a correspondence model for appearance only. We propose instead a convolutional neural network architecture, called SCNet, for learning a geometrically plausible model for semantic correspondence. SCNet uses region proposals as matching primitives, and explicitly incorporates geometric consistency in its loss function. It is trained on image pairs obtained from the PASCAL VOC 2007 keypoint dataset, and a comparative evaluation on several standard benchmarks demonstrates that the proposed approach substantially outperforms both recent deep learning architectures and previous methods based on hand-crafted features.Comment: ICCV 201

Real-Time Object Tracking via Meta-Learning: Efficient Model Adaptation and One-Shot Channel Pruning

We propose a novel meta-learning framework for real-time object tracking with efficient model adaptation and channel pruning. Given an object tracker, our framework learns to fine-tune its model parameters in only a few iterations of gradient-descent during tracking while pruning its network channels using the target ground-truth at the first frame. Such a learning problem is formulated as a meta-learning task, where a meta-tracker is trained by updating its meta-parameters for initial weights, learning rates, and pruning masks through carefully designed tracking simulations. The integrated meta-tracker greatly improves tracking performance by accelerating the convergence of online learning and reducing the cost of feature computation. Experimental evaluation on the standard datasets demonstrates its outstanding accuracy and speed compared to the state-of-the-art methods.Comment: 9 pages, 5 figures, AAAI 2020 accepte

Effects of Walking Promotion Using Smart Mobile Activity Meter on Changes in Metabolic Health

Background: Regular physical exercise can increase insulin sensitivity, improve good cholesterol levels, reduce body weight, and ameliorate cardiovascular risk factors. Over the past decade, e-health technologies using mobile applications were proven to be an effective delivery method for educational interventions. No e-health tools were designated specifically for patients with metabolic syndrome. Methods: Final analysis subjects were 7,234 as a result of excluding cases with missing values according to the variables used. We mediated the subjects to walk in advance, 3 months, and 6 months through smart mobile health care, and the level of improvement in the metabolic syndrome index was repeatedly measured. RM ANOVA & Path analysis & Sobel test was conducted to determine whether there was a mediating effect. Results: Subjects who practiced walking for up to 3 months tended to use smart mobile health care devices better for 6 months, and the walking practice rate increased. This confirmed that there was a significant partial mediating effect as a result of the Sobel test. after 6 months, WC and TG decrease. Conclusion: It was found that the more programs that provide advice and interventions on physical activity through smart mobile healthcare devices were used, the more helpful it was to promote walking exercise practice

A secure SNP panel scheme using homomorphically encrypted K-mers without SNP calling on the user side

Background Single Nucleotide Polymorphism (SNP) in the genome has become crucial information for clinical use. For example, the targeted cancer therapy is primarily based on the information which clinically important SNPs are detectable from the tumor. Many hospitals have developed their own panels that include clinically important SNPs. The genome information exchange between the patient and the hospital has become more popular. However, the genome sequence information is innate and irreversible and thus its leakage has serious consequences. Therefore, protecting ones genome information is critical. On the other side, hospitals may need to protect their own panels. There is no known secure SNP panel scheme to protect both. Results In this paper, we propose a secure SNP panel scheme using homomorphically encrypted K-mers without requiring SNP calling on the user side and without revealing the panel information to the user. Use of the powerful homomorphic encryption technique is desirable, but there is no known algorithm to efficiently align two homomorphically encrypted sequences. Thus, we designed and implemented a novel secure SNP panel scheme utilizing the computationally feasible equality test on two homomorphically encrypted K-mers. To make the scheme work correctly, in addition to SNPs in the panel, sequence variations at the population level should be addressed. We designed a concept of Point Deviation Tolerance (PDT) level to address the false positives and false negatives. Using the TCGA BRCA dataset, we demonstrated that our scheme works at the level of over a hundred thousand somatic mutations. In addition, we provide a computational guideline for the panel design, including the size of K-mer and the number of SNPs. Conclusions The proposed method is the first of its kind to protect both the users sequence and the hospitals panel information using the powerful homomorphic encryption scheme. We demonstrated that the scheme works with a simulated dataset and the TCGA BRCA dataset. In this study, we have shown only the feasibility of the proposed scheme and much more efforts should be done to make the scheme usable for clinical use.This research is supported by National Research Foundation of Korea (NRF) funded by the Ministry of Science, ICT (No. NRF-2017M3C4A7065887), The Collaborative Genome Program for Fostering New Post-Genome Industry of the National Research Foundation (NRF) funded by the Ministry of Science and ICT (MSIT) (No. NRF-2014M3C9A3063541), A grant of the Korea Health Technology R&D Project through the Korea Health Industry Development Institute (KHIDI), funded by the Ministry of Health & Welfare, Republic of Korea (grant number: HI15C3224), and Institute for Information & communications Technology Promotion (IITP) grant funded by the Korea government (MSIP) (B0717-16-0098, Development of homomorphic encryption for DNA analysis and biometry authentication). The publication cost will be paid by the Seoul National University Office of Research

Long-term risk of all-cause mortality in live kidney donors: a matched cohort study

Background Long-term outcomes of live kidney donors remain controversial, although this information is crucial for selecting potential donors. Thus, this study compared the long-term risk of all-cause mortality between live kidney donors and healthy control. Methods We performed a retrospective cohort study including donors from seven tertiary hospitals in South Korea. Persons who underwent voluntary health screening were included as controls. We created a matched control group considering age, sex, era, body mass index, baseline hypertension, diabetes, estimated glomerular filtration rate, and dipstick albuminuria. The study outcome was progression to end-stage kidney disease (ESKD), and all-cause mortality as identified in the linked claims database. Results We screened 1,878 kidney donors and 78,115 health screening examinees from 2003 to 2016. After matching, 1,701 persons remained in each group. The median age of the matched study subjects was 44 years, and 46.6% were male. Among the study subjects, 2.7% and 16.6% had underlying diabetes and hypertension, respectively. There were no ESKD events in the matched donor and control groups. There were 24 (1.4%) and 12 mortality cases (0.7%) in the matched donor and control groups, respectively. In the age-sex adjusted model, the risk for all-cause mortality was significantly higher in the donor group than in the control group. However, the significance was not retained after socioeconomic status was included as a covariate (adjusted hazard ratio, 1.82; 95% confidence interval, 0.87–3.80). Conclusion All-cause mortality was similar in live kidney donors and matched non-donor healthy controls with similar health status and socioeconomic status in the Korean population

Metabolic risks in living kidney donors in South Korea

Background Considering the growing prevalence of Western lifestyles and related chronic diseases occurring in South Korea, this study aimed to explore the progression of metabolic risk factors in living kidney donors. Methods This study enrolled living kidney donors from seven hospitals from 1982 to 2016. The controls were individuals that voluntarily received health check-ups from 1995 to 2016 that were matched with donors according to age, sex, diabetes status, baseline estimated glomerular filtration rate, and date of the medical record. Data on hyperuricemia, hypertension, hypercholesterolemia, and overweight/obesity were collected to determine metabolic risks. Logistic regressions with interaction terms between the medical record date and donor status were used to compare the trends in metabolic risks over time in the two groups. Results A total of 2,018 living kidney donors and matched non-donors were included. The median age was 44.0 years and 54.0% were women. The living kidney donors showed a lower absolute prevalence for all metabolic risk factors, except for those that were overweight/obese, than the non-donors. The proportion of subjects that were overweight/obese was consistently higher over time in the donor group. The changes over time in the prevalence of each metabolic risk were not significantly different between groups, except for a lower prevalence of metabolic risk factors ≥ 3 in donors. Conclusion Over time, metabolic risks in living kidney donors are generally the same as in non-donors, except for a lower prevalence of metabolic risk factors ≥3 in donors