This paper introduces a Mutual Information Independence Model (MIIM) and proposes a feature relaxation principle to resolve the data sparseness problem in MIIM-based named entity recognition via hierarchical features. In this way, a named entity recognition system with better performance and better portability can be achieved. Evaluation of our system on MUC-6 and MUC-7 English named entity tas...

Cross language-image retrieval is a problem of high interest that is at the frontier between computer vision and natural language processing. State-of-the-art methods learn a common space with regard to some constraints of correlation or similarity from two textual and visual modalities that are processed in parallel and possibly jointly. This paper proposes a different approach that considers ...

We present a photonic crystal slab (PCS) photodetector, designed for resonant absorption of infrared light in quantum wells. With the PCS it is possible to enhance the absorption efficiency by increasing photon lifetime in the detector active region. To design the optical properties of the device we simulate the PCS photonic band structure with the two-dimensional (2D) revised plane wave expans...

Image captioning is oriented towards describing an image with the best possible use of words that can provide a semantic, relatable meaning scenario inscribed. Different models be used to accomplish this arduous task depending on context and requirement what needs achieved. An encoder–decoder model which uses feature vectors as input encoder often marked one appropriate process. In proposed wor...

Biomass fuels play an important role in the field of fluidized bed combustion, but due to diversity and uncertainty fuels, there are usually some problems high CO emission that cannot be directly solved by combustion adjustment. In this paper, a 75 t/h biomass was taken as research object. It observed from test gas incomplete loss reached 12.13% when mono-combustion wheat straw conducted, conce...

Background and aims  EUS-guided biliary drainage (EUS-BD) and rendezvous (EUS-RV) are acceptable rescue options for patients with failed endoscopic retrograde cholangiopancreatography (ERCP). However, there are limited training opportunities at most centers owing to low case volumes. The existing models do not replicate the difficulties encountered during EUS-BD. We aimed to develop and validat...

In this paper, we present a multimodal Recurrent Neural Network (m-RNN) model for generating novel sentence descriptions to explain the content of images. It directly models the probability distribution of generating a word given previous words and the image. Image descriptions are generated by sampling from this distribution. The model consists of two sub-networks: a deep recurrent neural netw...

This paper reports a large-scale study that aims to understand how mobile application (app) vulnerabilities are associated with software libraries. We analyze both free and paid apps. Studying paid apps was quite meaningful because it helped us understand how differences in app development/maintenance affect the vulnerabilities associated with libraries. We analyzed 30k free and paid apps colle...

False alarms triggered by security sensors incur high costs for all parties involved. According to police reports, a large majority of alarms are false. Recent advances in machine learning can enable automatically classifying alarms. However, building a scalable alarm verification system is a challenge, since the system needs to: (1) process thousands of alarms in real-time, (2) classify false ...