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This work is about recommending the best journal for article submission to authors. The approach taken here is based on relevance determined through the application of neural network based natural language processing techniques to the abstracts of articles already accepted by journals. Title, keywords, and field of study are not needed in the approach outlined here. The significance of the relevancy of a journal is that an article published in a less relevant journal will have less exposure to the intended target audience, and consequently have less of an impact. The conceptual content contained in the abstracts of articles appearing in a journal can be used to characterize that journal. The main purpose of this work will be exploring neural network architectures for discovering and recommending appropriate journals to those seeking to publish their research. In this work, the current state of the art will be extended and a robust and generic article-to-journal matching tool for all publishers, using Web of Science data, is proposed and made public for the first time. [ABSTRACT FROM AUTHOR]

Lifetime is a key parameter in the design of routing protocols in energy-constrained wireless sensor networks (WSNs). Conventional single-path routing schemes may not be optimal in maximizing network lifetime. In this paper, we present a new routing algorithm based on the optimal number of hops to partition the path from the source to the sink. The algorithm is based on energy consumption constrained routing method. The mathematical model uses mixed-integer programming (MIP), based on the Lagrangian relaxation (LR) method, to define critical parameters that control the adaptive hop-by-hop switching. LINGO is used to investigate the performance trade-offs between energy efficiency and quality of service (QoS). Simulation results revealed that our algorithm significantly improves the lifetime by 46.91, 73.00, and 80.00 % as compared to the well-known node density control, upper-bound, and WSN optimization of network lifetime algorithms, respectively. [ABSTRACT FROM AUTHOR]