Localization technology is important for the development of indoor location-based services (LBS). Global Positioning System (GPS) becomes invalid in indoor environments due to the non-line-of-sight issue, so it is urgent to develop a real-time high-accuracy localization approach for smartphones. However, accurate localization is challenging due to issues such as real-time response requirements,...

the paper deals with data envelopment analysis (dea) and artificial neural network (ann). we believe that solving for the dea efficiency measure, simultaneously with neural network model, provides a promising rich approach to optimal solution. in this paper, a new neural network model is used to estimate the inefficiency of dmus in large datasets.

As a first experience in neural network modeling, and tensor flow usage, we try to implement a match-LSTM attention model, which is known for achieving interesting results on the SQuaD dataset leader board.

MXNet is a multi-language machine learning (ML) library to ease the development of ML algorithms, especially for deep neural networks. Embedded in the host language, it blends declarative symbolic expression with imperative tensor computation. It offers auto differentiation to derive gradients. MXNet is computation and memory efficient and runs on various heterogeneous systems, ranging from mob...

Neural collaborative filtering (NCF) [15] and recurrent recommender systems (RRN) [38] have been successful in modeling user-item relational data. However, they are also limited in their assumption of static or sequential modeling of relational data as they do not account for evolving users’ preference over time as well as changes in the underlying factors that drive the change in user-item rel...

geological facies interpretation is essential for reservoir studying. the method of classification and identification seismic traces is a powerful approach for geological facies classification and distinction. use of neural networks as classifiers is increasing in different sciences like seismic. they are computer efficient and ideal for patterns identification. they can simply learn new algori...

INTRODUCTION : Mapping white matter fiber pathways in central nervous system (CNS) is important for the understanding of neural transmission and brain organization in general. In this study, we propose a non-diffusion based method for tracking a magnetic network existing in brain white matter. The proposed method utilizes a previously unexplored magnetic property of white matter fibers. We foun...