The ecological footprint and economic performance of the current suite biofuel production methods make them insufficient to displace fossil fuels reduce their impact on inventory Green House Gas (GHG) in global atmosphere. Algae metabolic engineering forms basis for 4th generation which can meet this need. first biofuels are known be made from agricultural products such as corn or sugarcane. second use all (lingo)cellulosic biomass. third fourth involves “algae-to-biofuels” technology:...

Deep Neural Networks (DNNs) are typically trained by backpropagation in a batch setting, requiring the entire training data to be made available prior learning task. This is not scalable for many real-world scenarios where new arrives sequentially stream. We aim address an open challenge of ``Online Learning" (ODL) DNNs on fly online setting. Unlike traditional that often optimizes some convex objective function with respect shallow model (e.g., linear/kernel-based hypothesis), ODL more...

Image-text matching tasks have recently attracted a lot of attention in the computer vision field. The key point this cross-domain problem is how to accurately measure similarity between visual and textual contents, which demands fine understanding both modalities. In paper, we propose novel position focused network (PFAN) investigate relation views. work, integrate object clue enhance visual-text joint-embedding learning. We first split images into blocks, by infer relative region image....

Online learning represents an important family of machine algorithms, in which a learner attempts to resolve online prediction (or any type decision-making) task by model/hypothesis from sequence data instances one at time. The goal is ensure that the would make accurate predictions correct decisions) given knowledge answers previous or tasks and possibly additional information. This contrast many traditional batch offline algorithms are often designed train model collection training...

Bug reports document unexpected software behaviors experienced by users. To be effective, they should allow bug triagers to easily understand and reproduce the potential reported bugs, clearly describing Observed Behavior (OB), Steps Reproduce (S2R), Expected (EB). Unfortunately, while considered extremely useful, reporters often miss such pieces of information in and, date, there is no effective way automatically check enforce their presence. We manually analyzed nearly 3k what extent OB,...

The relationship of rotatable bond count (N(rot)) and polar surface area (PSA) with oral bioavailability in rats was examined for 434 Pharmacia compounds compared an earlier report from Veber et al. (J. Med. Chem. 2002, 45, 2615). N(rot) PSA were calculated QikProp or Cerius2. resulting correlations depended on the calculation method therapeutic class within data superset. These results underscore that such generalizations must be used caution.

While joint models have been developed for many NLP tasks, the vast majority of event coreference resolvers, including top-performing resolvers competing in recent TAC KBP 2016 Event Nugget Detection and Coreference task, are pipeline-based, where propagation errors from trigger detection component to is a major performance limiting factor. To address this problem, we propose model jointly learning coreference, detection, anaphoricity. Our novel its choice tasks features capturing cross-task...

Recent years have seen a gradual shift of focus from entity-based tasks to event-based in information extraction research. Being core task, event coreference resolution is less studied but arguably more challenging than entity resolution. This paper provides an overview the major milestones made research since its inception two decades ago.

Image and sentence matching has attracted increasing attention since it is associated with two important modalities of vision language. Previous methods aim to find the latent correspondences between image regions words by aggregating similarities region-word pairs. However, these approaches consider little about relationships diverse in treat all pairs equally. Moreover, focusing on fine-grained alignment overly, true meaning original will be likely distorted. In this paper, a novel Region...

Yin Jou Huang, Jing Lu, Sadao Kurohashi, Vincent Ng. Proceedings of the 2019 Conference North American Chapter Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long and Short Papers). 2019.

Bi-directional image-text retrieval and matching attract much attention recently. This cross-domain task demands a fine understanding of both modalities for learning measure different modality data. In this paper, we propose novel position focused network to investigate the relation between visual textual views. work integrates prior object enhance visual-text joint-embedding learning. The image is first split into blocks, which are treated as basic cells, an region inferred. Then, model...

Precise object counting is crucial in practical applications, finding extensive utility across numerous societal domains. In the context of few-shot counting, variations angles can significantly alter distribution and distinguishability feature points, thereby increasing difficulty extraction. To address these challenges, a spatial channel similarity-aware attention-enhancement network for scenarios introduced. The employs slice convolution attention mechanisms within dimensions,...

Defocus deblurring is a challenging task in the fields of computer vision and image processing. The irregularity defocus blur kernels, coupled with limitations computational resources, poses significant difficulties for defocused restoration. Additionally, varying degrees across different regions impose higher demands on feature capture. Insufficient fine-grained extraction can result artifacts loss details, while inadequate coarse-grained cause distortion unnatural transitions. To address...

Deep image embedding aims at learning a convolutional neural network (CNN) based mapping function that maps an to feature vector. The quality is usually evaluated by the performance in search tasks. Since very few users bother open second page results, top-k precision mostly dominates user experience and thus one of crucial evaluation metrics for quality. Despite being extensively studied, existing algorithms are on heuristic observation without theoretical guarantee. Consequently, gradient...

Polydopamine (PDA) depositions, inspired by mussel foot adhesive proteins, represent a versatile method for preparing separation membranes. However, PDA-based nanofiltration membranes are limited the long preparation time and moderate flux. This work modulated PDA deposition processes with spiro-piperazine (SPIP) molecule containing two secondary amine groups quaternary ammonium salt. The SPIP could be covalently inserted into coating structures via Michael addition reaction to accelerate...

We propose a neural event coreference model in which is jointly trained with five tasks: trigger detection, entity coreference, anaphoricity determination, realis and argument extraction. To guide the learning of this complex model, we incorporate cross-task consistency constraints into process as soft via designing penalty functions. In addition, novel idea viewing single task, believe step towards unified resolution. The resulting achieves state-of-the-art results on KBP 2017 dataset.

Despite the significant progress on entity coreference resolution observed in recent years, there is a general lack of understanding what has been improved. We present an empirical analysis state-of-the-art resolvers with goal providing NLP audience better state art and researchers directions for future research.