Backbone Can Not be Trained at Once: Rolling Back to Pre-trained Network for Person Re-Identification

In person re-identification (ReID) task, because of its shortage of trainable dataset, it is common to utilize fine-tuning method using a classification network pre-trained on a large dataset. However, it is relatively difficult to sufficiently fine-tune the low-level layers of the network due to the gradient vanishing problem. In this work, we propose a novel fine-tuning strategy that allows low-level layers to be sufficiently trained by rolling back the weights of high-level layers to their initial pre-trained weights. Our strategy alleviates the problem of gradient vanishing in low-level layers and robustly trains the low-level layers to fit the ReID dataset, thereby increasing the performance of ReID tasks. The improved performance of the proposed strategy is validated via several experiments. Furthermore, without any add-ons such as pose estimation or segmentation, our strategy exhibits state-of-the-art performance using only vanilla deep convolutional neural network architecture.Comment: Accepted to AAAI 201

Congener Profiles and Source-Wise Phase Partitioning Analysis of PCDDs/Fs and PCBs in Gyeonggi-Do Ambient Air, South Korea

The atmospheric concentrations and gas–particle partitioning of polychlorinated dibenzo-p-dioxins and furans (PCDDs/Fs) and polychlorinated biphenyls (PCBs) were investigated at two sites (Suwon and Ansan) in Gyeonggi-do, a heavily industrialized area of Korea, during the year 2010. The sum level (Σ17) of PCDDs/Fs and dioxin-like PCBs (dl-PCBs) in the ambient air at Suwon and Ansan ranged from 0.04 to 0.30 pg-TEQ·m−3 (geometric mean: 0.09 pg-TEQ·m−3) and 0.17 to 0.63 pg-TEQ·m−3 (geometric mean: 0.36 pg-TEQ·m−3), respectively. Moreover, the geometric mean concentrations of Σ180 PCBs at Suwon and Ansan were 233.6 pg·m−3 and 274.2 pg·m−3, respectively, and di-chlorinated biphenyls and tri-chlorinated biphenyls were the predominant homologs. Among the PCB congeners, 3,3\u27-dichlorobiphenyl (PCB-11) was the dominant species at both sites during all sampling periods, comprising up to 15.1% of Σ180 PCBs at Ansan and 24.6% at Suwon. We evaluated their gas-to-particle equilibriums by conducting regression between the particle–gas partition coefficient Kp (m3·ug−1) and the corresponding subcooled liquid vapor pressure (PL°). The slope (m) values for log–log plots of Kp vs. PL° were steeper in industrial areas owing to local source proximity. Moreover, owing to enhanced emissions from combustion-related sources at low temperatures, PCDD/Fs exhibited the largest deviation from the regression line of the particle–gas partition coefficient. Incinerators were found to be the primary emission source of atmospheric PCDDs/Fs, whereas re-evaporation from pre-existing environmental loads (e.g., storage areas or spilled soil and water bodies) was the dominant source for PCBs

ICEM2010-40201 CHARACTERIZATION OF RADIOACTIVE WASTE FROM SIDE STRUCTURAL COMPONENTS OF A CANDU REACTOR FOR DECOMMISSIONING APPLICATIONS IN KOREA

ABSTRACT Reactor core components and structural materials of nuclear power plants to be decommissioned have been irradiated by neutrons of various intensities and spectrum. This long term irradiation results in the production of large number of radioactive isotopes that serve as a source of radioactivity for thousands of years for future. Decommissioning of a nuclear reactor is a costly program comprising of dismantling, demolishing of structures and waste classification for disposal applications. The estimate of radio-nuclides and radiation levels forms the essential part of the whole decommissioning program. It can help establishing guidelines for the waste classification, dismantling and demolishing activities. ORIGEN2 code has long been in use for computing radionuclide concentrations in reactor cores and near core materials for various burn-up-decay cycles, using one-group collapsed cross sections. Since ORIGEN2 assumes a constant flux and nuclide capture cross-sections in all regions of the core, uncertainty in its results could increase as region of interest goes away from the core. This uncertainty can be removed by using a Monte Carlo Code, like MCNP, for the correct calculations of flux and capture cross-sections inside the reactor core and in far core regions. MCNP has greater capability to model the reactor problems in much realistic way that is to incorporate geometrical, compositional and spectrum information. In this paper the classification of radioactive waste from the side structural components of a CANDU reactor is presented. MCNP model of full core was established because of asymmetric structure of the reactor. Side structural components of total length 240 cm and radius 16.122 cm were modeled as twelv

Rollback Ensemble With Multiple Local Minima in Fine-Tuning Deep Learning Networks

Image retrieval is a challenging problem that requires learning generalized features enough to identify untrained classes, even with very few classwise training samples. In this article, to obtain generalized features further in learning retrieval data sets, we propose a novel fine-tuning method of pretrained deep networks. In the retrieval task, we discovered a phenomenon in which the loss reduction in fine-tuning deep networks is stagnated, even while weights are largely updated. To escape from the stagnated state, we propose a new fine-tuning strategy to roll back some of the weights to the pretrained values. The rollback scheme is observed to drive the learning path to a gentle basin that provides more generalized features than a sharp basin. In addition, we propose a multihead ensemble structure to create synergy among multiple local minima obtained by our rollback scheme. Experimental results show that the proposed learning method significantly improves generalization performance, achieving state-of-the-art performance on the Inshop and SOP data sets.N

A Cross-Correlation-Based Approach to Pattern Distortion and Mutual Coupling for Shared-Aperture Antennas

Featured Application</p> Although the proposed method is originally used for shared-aperture antennas that are composed of multiple antennas operating in different frequency bands for various applications, such as radar, electronic warfare, and communications, we think that the proposed approach can also be extended to any application where both mutual coupling and platform effects seriously affect antenna characteristics.</p> This paper proposes a pattern distortion coefficient as a new figure of merit to quantitatively evaluate both mutual coupling and pattern distortions in multi-antenna systems. The proposed coefficient is defined as a cross correlation between unaffected and affected far-field patterns of antennas under test, and the input patterns are weighted using a Gaussian function to consider the target operation angle. The feasibility of the proposed approach is validated using a two-antenna system composed of an inverted-F antenna and a microstrip patch antenna, and the amount of mutual coupling is adjusted by changing the distance between the two antennas. The evaluation is further extended to a single-antenna system with a conducting wall that produces strong platform effects with serious pattern distortions. The results demonstrate that the proposed figure of merit provides quantitative insight into the amplitude and phase distortions of far-field patterns that can be caused by both mutual coupling and platform effects.</p&gt

Motion-aware ensemble of three-mode trackers for unmanned aerial vehicles

To tackle problems arising from unexpected camera motions in unmanned aerial vehicles (UAVs), we propose a three-mode ensemble tracker where each mode specializes in distinctive situations. The proposed ensemble tracker is composed of appearance-based tracking mode, homography-based tracking mode, and momentum-based tracking mode. The appearance-based tracking mode tracks a moving object well when the UAV is nearly stopped, whereas the homography-based tracking mode shows good tracking performance under smooth UAV or object motion. The momentum-based tracking mode copes with large or abrupt motion of either the UAV or the object. We evaluate the proposed tracking scheme on a widely-used UAV123 benchmark dataset. The proposed motion-aware ensemble shows a 5.3% improvement in average precision compared to the baseline correlation filter tracker, which effectively employs deep features while achieving a tracking speed of at least 80fps in our experimental settings. In addition, the proposed method outperforms existing real-time correlation filter trackers.N

Instant formation of horizontally ordered nanofibrous hydrogel films and direct investigation of peculiar neuronal cell behaviors atop.

BACKGROUND: Hydrogels have been widely used in many research fields owing to optical transparency, good biocompatibility, tunable mechanical properties, etc. Unlike typical hydrogels in the form of an unstructured bulk material, we developed aqueous dispersions of fiber-shaped hydrogel structures with high stability under ambient conditions and their application to various types of transparent soft cell culture interfaces with anisotropic nanoscale topography. METHOD: Nanofibers based on the polyvinyl alcohol and polyacrylic acid mixture were prepared by electrospinning and hydrogelified to nano-fibrous hydrogels (nFHs) after thermal crosslinking and sulfuric acid treatment. By modifying various material surfaces with positively-charged polymers, negatively-charged superabsorbent nFHs could be selectively patterned by employing micro-contact printing or horizontally aligned by applying shear force with a wired bar coater. RESULTS: The angular distribution of bar-coated nFHs was dramatically reduced to ± 20° along the applied shear direction unlike the drop-coated nFHs which exhibit random orientations. Next, various types of cells were cultured on top of transparent soft nFHs which showed good viability and attachment while their behaviors could be easily monitored by both upright and inverted optical microscopy. Particularly, neuronal lineage cells such as PC 12 cells and embryonic hippocampal neurons showed highly stretched morphology along the overall fiber orientation with aspect ratios ranging from 1 to 14. Furthermore, the resultant neurite outgrowth and migration behaviors could be effectively controlled by the horizontal orientation and the three-dimensional arrangement of underlying nFHs, respectively. CONCLUSION: We expect that surface modifications with transparent soft nFHs will be beneficial for various biological/biomedical studies such as fundamental cellular studies, neuronal/stem cell and/or organoid cultures, implantable probe/device coatings, etc

A study on the performance of the Donation Improvement Program in Korea

Background : The Donation Improvement Program (DIP) is intended to increase organ donation at hospitals. The program includes education for healthcare professionals of participating hospitals about each step of donation as well as evaluation. The DIP consists of medical record review (MRR) and a Hospital Attitude Survey (HAS). The purpose of this study was to evaluate the DIP results for the last 7 years. Methods : For MRR, we analyzed 58,385 cases of mortality from 77 hospitals between 2012 and 2018. The HAS data for the degree of education experience, competence, and knowledge related to brain death (BD) and donation were analyzed from 23 DIP-participating hospitals in 2012 and 51 DIP-participating hospitals in 2015 and 2018 each. Results : The recognition rate of potential BD was 24.9%, 61.3%, and 73.2%, and donation rate was 7.5%, 11.7%, and 15.8% at 6 months before, 1–2 years after, and 4–5 years after the agreement, respectively. Hospital staff with the necessary competence or knowledge to explain BD constituted 44.0% in 2012, while this increased to 62.8% in 2018. Conclusions: The DIP could increase the recognition of BD and the organ donation rate, and positively affect the attitudes of healthcare professionals toward organ donation. Spreading the DIP to all hospitals is urgent to increase organ donation