Harnessing Context for Budget-Limited Crowdsensing with Massive Uncertain Workers

Crowdsensing is an emerging paradigm of ubiquitous sensing, through which a crowd of workers are recruited to perform sensing tasks collaboratively. Although it has stimulated many applications, an open fundamental problem is how to select among a massive number of workers to perform a given sensing task under a limited budget. Nevertheless, due to the proliferation of smart devices equipped with various sensors, it is very difficult to profile the workers in terms of sensing ability. Although the uncertainties of the workers can be addressed by standard Combinatorial Multi-Armed Bandit (CMAB) framework through a trade-off between exploration and exploitation, we do not have sufficient allowance to directly explore and exploit the workers under the limited budget. Furthermore, since the sensor devices usually have quite limited resources, the workers may have bounded capabilities to perform the sensing task for only few times, which further restricts our opportunities to learn the uncertainty. To address the above issues, we propose a Context-Aware Worker Selection (CAWS) algorithm in this paper. By leveraging the correlation between the context information of the workers and their sensing abilities, CAWS aims at maximizing the expected total sensing revenue efficiently with both budget constraint and capacity constraints respected, even when the number of the uncertain workers are massive. The efficacy of CAWS can be verified by rigorous theoretical analysis and extensive experiments

VibHead: An Authentication Scheme for Smart Headsets through Vibration

Recent years have witnessed the fast penetration of Virtual Reality (VR) and Augmented Reality (AR) systems into our daily life, the security and privacy issues of the VR/AR applications have been attracting considerable attention. Most VR/AR systems adopt head-mounted devices (i.e., smart headsets) to interact with users and the devices usually store the users' private data. Hence, authentication schemes are desired for the head-mounted devices. Traditional knowledge-based authentication schemes for general personal devices have been proved vulnerable to shoulder-surfing attacks, especially considering the headsets may block the sight of the users. Although the robustness of the knowledge-based authentication can be improved by designing complicated secret codes in virtual space, this approach induces a compromise of usability. Another choice is to leverage the users' biometrics; however, it either relies on highly advanced equipments which may not always be available in commercial headsets or introduce heavy cognitive load to users. In this paper, we propose a vibration-based authentication scheme, VibHead, for smart headsets. Since the propagation of vibration signals through human heads presents unique patterns for different individuals, VibHead employs a CNN-based model to classify registered legitimate users based the features extracted from the vibration signals. We also design a two-step authentication scheme where the above user classifiers are utilized to distinguish the legitimate user from illegitimate ones. We implement VibHead on a Microsoft HoloLens equipped with a linear motor and an IMU sensor which are commonly used in off-the-shelf personal smart devices. According to the results of our extensive experiments, with short vibration signals ($\leq 1s$), VibHead has an outstanding authentication accuracy; both FAR and FRR are around 5%

Observational energy transfers of a spiral cold filament within an anticyclonic eddy

The ocean surface mixed layer represents a critical interface linking the ocean and atmosphere. The physical processes determining the surface mixed layer properties and mediate atmosphere-ocean exchange. Submesoscale processes play a key role in cross-scale oceanic energy transformation and the determination of surface mixed-layer properties, including the enhancement of vertical nutrient transport, leading to increased primary productivity. Herein, we presented observations of the spiral chlorophyll-a filament and its influence on turbulence within an anticyclonic eddy in the western South China Sea during August 2021. The filament had a negative Ertel potential vorticity associated with strong upwelled/downward currents (approximately 20-40 m/day). Across-filament sections of the in-situ profiles showed turbulent dissipation rates enhanced in the filament. We suggested this enhancement values can be attributed to submesoscale processes, which accounted for 25% of the total parameterized turbulent dissipation rates. The present parametrized submesoscale turbulent scheme overestimated the in-situ values. The filament transferred kinetic energy upward to anticyclonic eddy via barotropic instability and gained energy from the anticyclonic eddy via baroclinic instability. After kinetic energy budget diagnostic, we suggested besides symmetric instability, centrifugal instability and mixed layer baroclinic instability should also be included in the turbulence scheme to overcome the overestimation. The observed dual energy transfers between the anticyclonic eddy and filament, and the observed high turbulent energy dissipation within the filament, emphasized the need for these processes to be accurately parameterized regional and climate models

Undiagnosed diabetic retinopathy in Northeast China: prevalence and determinants

ObjectiveTo report the prevalence and contributing factors of undiagnosed diabetic retinopathy (DR) in a population from Northeastern China.Subjects/MethodsA total of 800 subjects from the Fushun Diabetic Retinopathy Cohort Study were enrolled. A questionnaire assessing incentives and barriers to diagnosis of DR was administered. Logistic regression was used to identify clinical and sociodemographic factors associated with undiagnosed DR. In a prespecified subgroup analysis, we divided patients into vision-threatening diabetic retinopathy (VTDR) and non-VTDR (NVTDR) subgroups.ResultsAmong 800 participants with DR, 712 (89.0%) were undiagnosed. Among 601 with NVTDR, 566 (94.2%) were undiagnosed. Among 199 with VTDR, 146 (73.4%) were undiagnosed. The risk factors affecting the timely diagnosis of NVTDR and VTDR exhibit significant disparities. In multivariate models, factors associated with undiagnosed VTDR were age over 60 years (OR = 2.966; 95% CI = 1.205-7.299; P = 0.018), duration of diabetes over 10 years (OR = 0.299; 95% CI = 0.118-0753; P = 0.010), visual impairment or blindness (OR = 0.310; 95% CI = 0.117-0.820; P = 0.018), receiving a reminder to schedule an eye examination (OR = 0.380; 95% CI = 0.163-0.883; P = 0.025), and the belief that “people with diabetes are unlikely to develop an eye disease” (OR = 4.691; 95% CI = 1.116-19.724; P = 0.035). However, none of the factors were associated with undiagnosed NVTDR (all P ≥ 0.145).ConclusionOur research has uncovered a disconcerting trend of underdiagnosis in cases of DR within our population. Addressing determinants of undiagnosed DR may facilitate early detection

Characterization of Non-heading Mutation in Heading Chinese Cabbage (Brassica rapa L. ssp. pekinensis)

Heading is a key agronomic trait of Chinese cabbage. A non-heading mutant with flat growth of heading leaves (fg-1) was isolated from an EMS-induced mutant population of the heading Chinese cabbage inbred line A03. In fg-1 mutant plants, the heading leaves are flat similar to rosette leaves. The epidermal cells on the adaxial surface of these leaves are significantly smaller, while those on the abaxial surface are much larger than in A03 plants. The segregation of the heading phenotype in the F2 and BC1 population suggests that the mutant trait is controlled by a pair of recessive alleles. Phytohormone analysis at the early heading stage showed significant decreases in IAA, ABA, JA and SA, with increases in methyl IAA and trans-Zeatin levels, suggesting they may coordinate leaf adaxial-abaxial polarity, development and morphology in fg-1. RNA-sequencing analysis at the early heading stage showed a decrease in expression levels of several auxin transport (BrAUX1, BrLAXs, and BrPINs) and responsive genes. Transcript levels of important ABA responsive genes, including BrABF3, were up-regulated in mid-leaf sections suggesting that both auxin and ABA signaling pathways play important roles in regulating leaf heading. In addition, a significant reduction in BrIAMT1 transcripts in fg-1 might contribute to leaf epinastic growth. The expression profiles of 19 genes with known roles in leaf polarity were significantly different in fg-1 leaves compared to wild type, suggesting that these genes might also regulate leaf heading in Chinese cabbage. In conclusion, leaf heading in Chinese cabbage is controlled through a complex network of hormone signaling and abaxial-adaxial patterning pathways. These findings increase our understanding of the molecular basis of head formation in Chinese cabbage

A sustained ocean observing system in the Indian Ocean for climate related scientific knowledge and societal needs

© The Author(s), 2019. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Hermes, J. C., Masumoto, Y., Beal, L. M., Roxy, M. K., Vialard, J., Andres, M., Annamalai, H., Behera, S., D'Adamo, N., Doi, T., Peng, M., Han, W., Hardman-Mountford, N., Hendon, H., Hood, R., Kido, S., Lee, C., Lees, T., Lengaigne, M., Li, J., Lumpkin, R., Navaneeth, K. N., Milligan, B., McPhaden, M. J., Ravichandran, M., Shinoda, T., Singh, A., Sloyan, B., Strutton, P. G., Subramanian, A. C., Thurston, S., Tozuka, T., Ummenhofer, C. C., Unnikrishnan, A. S., Venkatesan, R., Wang, D., Wiggert, J., Yu, L., & Yu, W. (2019). A sustained ocean observing system in the Indian Ocean for climate related scientific knowledge and societal needs. Frontiers in Marine Science, 6, (2019): 355, doi: 10.3389/fmars.2019.00355.The Indian Ocean is warming faster than any of the global oceans and its climate is uniquely driven by the presence of a landmass at low latitudes, which causes monsoonal winds and reversing currents. The food, water, and energy security in the Indian Ocean rim countries and islands are intrinsically tied to its climate, with marine environmental goods and services, as well as trade within the basin, underpinning their economies. Hence, there are a range of societal needs for Indian Ocean observation arising from the influence of regional phenomena and climate change on, for instance, marine ecosystems, monsoon rains, and sea-level. The Indian Ocean Observing System (IndOOS), is a sustained observing system that monitors basin-scale ocean-atmosphere conditions, while providing flexibility in terms of emerging technologies and scientificand societal needs, and a framework for more regional and coastal monitoring. This paper reviews the societal and scientific motivations, current status, and future directions of IndOOS, while also discussing the need for enhanced coastal, shelf, and regional observations. The challenges of sustainability and implementation are also addressed, including capacity building, best practices, and integration of resources. The utility of IndOOS ultimately depends on the identification of, and engagement with, end-users and decision-makers and on the practical accessibility and transparency of data for a range of products and for decision-making processes. Therefore we highlight current progress, issues and challenges related to end user engagement with IndOOS, as well as the needs of the data assimilation and modeling communities. Knowledge of the status of the Indian Ocean climate and ecosystems and predictability of its future, depends on a wide range of socio-economic and environmental data, a significant part of which is provided by IndOOS.This work was supported by the PMEL contribution no. 4934