565 research outputs found
Genotype and environment interaction and stability analysis for seed yield in yellow mung bean (Vigna radiata L.)
Nine yellow seeded mung (Vigna radiata L.) genotypes were evaluated along with three checks for their yield performance during three years (2007, 2010 and 2011). Pooled analysis of variance and stability analysis were performed. The genotypic (G) × environment (E) interaction and both variance due to genotypes and environment were significant. The portioning of G × E interaction into linear and non-linear components indicated that both predictable and unpredictable components shared the interaction. On the basis of stability parameters, the top yielding genotypes such as BGS-9 (605.444 Kg/Ha), Sel-4 (519.778 Kg/Ha) and China mung (567.000 Kg/Ha) exhibited high mean yield. Based on stability parameters the genotypes YM-5 (459.889 Kg/Ha), YM-8 (451.333 Kg/Ha) exhibited low mean performance along with regression value nearer to unity (bi=1) and non significant deviation from regression (S2 di=0) indicating the high stability and wider adaptability across the three environments. The genotypes BGS-9 (605.444 Kg/Ha) and Sel-4 (519.778 Kg/Ha) exhibited high mean value and bi values (bi>1) and non significant deviation (S2 di < 0) value indicating adapted for high performance environments (These genotypes are sensitive to environments and give maximum yield when inputs are not limited)
Sample-Efficient Model-Free Reinforcement Learning with Off-Policy Critics
Value-based reinforcement-learning algorithms provide state-of-the-art
results in model-free discrete-action settings, and tend to outperform
actor-critic algorithms. We argue that actor-critic algorithms are limited by
their need for an on-policy critic. We propose Bootstrapped Dual Policy
Iteration (BDPI), a novel model-free reinforcement-learning algorithm for
continuous states and discrete actions, with an actor and several off-policy
critics. Off-policy critics are compatible with experience replay, ensuring
high sample-efficiency, without the need for off-policy corrections. The actor,
by slowly imitating the average greedy policy of the critics, leads to
high-quality and state-specific exploration, which we compare to Thompson
sampling. Because the actor and critics are fully decoupled, BDPI is remarkably
stable, and unusually robust to its hyper-parameters. BDPI is significantly
more sample-efficient than Bootstrapped DQN, PPO, and ACKTR, on discrete,
continuous and pixel-based tasks. Source code:
https://github.com/vub-ai-lab/bdpi.Comment: Accepted at the European Conference on Machine Learning 2019 (ECML
Exploiting Cognitive Structure for Adaptive Learning
Adaptive learning, also known as adaptive teaching, relies on learning path
recommendation, which sequentially recommends personalized learning items
(e.g., lectures, exercises) to satisfy the unique needs of each learner.
Although it is well known that modeling the cognitive structure including
knowledge level of learners and knowledge structure (e.g., the prerequisite
relations) of learning items is important for learning path recommendation,
existing methods for adaptive learning often separately focus on either
knowledge levels of learners or knowledge structure of learning items. To fully
exploit the multifaceted cognitive structure for learning path recommendation,
we propose a Cognitive Structure Enhanced framework for Adaptive Learning,
named CSEAL. By viewing path recommendation as a Markov Decision Process and
applying an actor-critic algorithm, CSEAL can sequentially identify the right
learning items to different learners. Specifically, we first utilize a
recurrent neural network to trace the evolving knowledge levels of learners at
each learning step. Then, we design a navigation algorithm on the knowledge
structure to ensure the logicality of learning paths, which reduces the search
space in the decision process. Finally, the actor-critic algorithm is used to
determine what to learn next and whose parameters are dynamically updated along
the learning path. Extensive experiments on real-world data demonstrate the
effectiveness and robustness of CSEAL.Comment: Accepted by KDD 2019 Research Track. In Proceedings of the 25th ACM
SIGKDD International Conference on Knowledge Discovery & Data Mining (KDD'19
Low-cost, Multispectral Imaging Mini-microscope for Longitudinal Oximetry in Small Animals
No abstract available
Fourier ptychography: current applications and future promises
Traditional imaging systems exhibit a well-known trade-off between the resolution and the field of view of their captured images. Typical cameras and microscopes can either “zoom in” and image at high-resolution, or they can “zoom out” to see a larger area at lower resolution, but can rarely achieve both effects simultaneously. In this review, we present details about a relatively new procedure termed Fourier ptychography (FP), which addresses the above trade-off to produce gigapixel-scale images without requiring any moving parts. To accomplish this, FP captures multiple low-resolution, large field-of-view images and computationally combines them in the Fourier domain into a high-resolution, large field-of-view result. Here, we present details about the various implementations of FP and highlight its demonstrated advantages to date, such as aberration recovery, phase imaging, and 3D tomographic reconstruction, to name a few. After providing some basics about FP, we list important details for successful experimental implementation, discuss its relationship with other computational imaging techniques, and point to the latest advances in the field while highlighting persisting challenges
DESIGN OF HIGH SPEED LESS AREA RADIX 2 AND RADIX 4 BOOTH SIGNED MULTIPLIER
This study presents the form and performance of restricted configurable Booth encoding multiplier for both witnessed and unregistered 32-bit numbers repeating & the hovering tend multiplication. Multiplication action is a usually used in many mathematical and beacon processing applications. An area valuable performance of a pumped-up configurable Radix-4 Booth multiplier with 3:2 compressors is devised & implemented on FPGA. Thus it provides amenable computation strength and a correct crop fidelity and high boost, dab area drinking. The form also dynamically disables the switching surgery of the not forceful knowledge ranges. Thus the inactive circuits perchance completely deactivated, with contracting prestige decrease and accelerating the further of effort. Thus the scheduled device of multiplier outperforms the typical multiplier in terms of area and further efficiencies. The scheduled produce has been implemented on FPGA Spartan 6 XC6SLX9 principle providing with a correlation of basics utilized and implementation boosts
Cultures of conflict:Protests, violent repression, and community values
What are the cultural origins of societal conflicts that revolve around democratization, women’s rights, and modern libertarian values? We propose that deep-seated differences in community-based collective values (at the micro-level) may be related to why people support anti-government protest and why they support repression of such protests (at the macro-level). The hypothesis was examined among residents of Turkey (N = 500). Cultural values, measured at the individual level and community level with the community collectivism scale, correlated with political orientation and emotions, as well as with subsequent support for anti-governmental protest or its repression. The main conclusions are that both support for protest and support for repression are related to the cultural values people hold and their subsequent political orientations and emotions. Micro-level cultural values in local communities may thus play a role in explaining macro-level socio-political divides
Radiação ultravioleta C no controle de Aspergillus flavus Link e de outros contaminantes da castanha-do-brasil.
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